#CABIN VERIFICATION AND VALIDATION - HABITAT DATA
Environment and Climate Change Canada
Analysis performed on 2019-08-13 14:16:14
This report presents the results of the verification and validation of a CABIN habitat data file associated to the project ****.
In this analysis, the habitat dataset is checked to answer the following question:
This document is a R notebook written in R Markdown. When you execute the code embedded in the notebook, the results will appear under the corresponding code. To do this, place your cursor inside a chunk (box which contains R code) and click the green arrow to the right of it named Run Current Chunk or press Ctrl+Shift+Enter (Cmd+Shift+Enter in macOS) on your keyboard. Repeat for each chunk. As the code contained in this notebook is executed, the results will appear under each of the corresponding chunks in this window. Once all commands are executed, click the Preview button at the top left of this window or press the Ctrl+Shift+K keys (Cmd+Shift+K in macOS). A new window will appear and will contain the report of these verification and validation results for the general CABIN data.
##Requirements
This notebook assumes that you have imported your data into R using the import notebook (CABIN_vv_import.Rmd).
The dataset containing habitat data for this project is present.
##Descriptive Statistics
The data file contains 458 visits (lines) and 89 variables (columns).
The following table presents a subset of the data.
Reading General Data
Check the data and make sure it reflects reality. Consider the following:
- Does the file seem to have been read correctly?
- Are columns missing?
List of visits present in the habitat data (ID from the CABIN database):
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458
*Check the data and make sure it reflects reality. Compare the list above with the following table which shows the visits from all the data for this project.
Variables List:
Altitude, StreamOrder, DistanceFromSource, Depth.Avg, Depth.BankfullMinusWetted, Depth.Max, Discharge, Macrophyte, Reach.CanopyCoverage, Reach.Logging, Reach.DomStreamsideVeg, Reach.Pools, Reach.Rapids, Reach.Riffles, Reach.StraightRun, Slope, Veg.Coniferous, Veg.Deciduous, Veg.GrassesFerns, Veg.Shrubs, Velocity.Avg, Velocity.Max, Width.Bankfull, Width.Wetted, XSEC.VelEquationSlope, XSEC.VelInstrumentDirect, XSEC.VelMethod, XSEC.VeloEquationIntercept, Rainfall01_JAN, Rainfall06_JUN, Snowfall06_JUN, SnowfallTotal_ANNUAL, Temp01_JANMax, Lake, Drainage.Area, StreamDensity, Reg.Alpine, Reg.Forest, Reg.Lake, Reg.UnregenForest, Reg.Wetland, Al, As, B, Mg, Ni, Bedrock, Boulder, Cobble, Gravel, Pebble, Sand, Silt.Clay, D50, Dg, Dominant.1st, Dominant.2nd, Embeddedness, PeriphytonCoverage, SurroundingMaterial, SlopeAvg, Ag, Al.1, Ba, CO3, General.Alkalinity, General.CarbonDOC, General.Colour, General.Conductivity, General.DO, General.pH, General.SolidsTDS, General.SolidsTSS, General.SpCond, General.TempAir, General.TempWater, General.Turbidity, Ni.1, Nitrogen.NH3, Nitrogen.NO2, Nitrogen.NO2.NO3, Nitrogen.NO3, Nitrogen.TDN, Nitrogen.TN, Nitrogen.TN_Organic, Phosphorus.OrthoP, Phosphorus.TDP, Phosphorus.TP, S
*Check the variables above and make sure they are all present.
###General Statistics
The following tables show the main general parameters per variable. When the result on the BinaryData line of the array is TRUE, this indicates that the variable has binary data. However, this result can also be obtained because the variable has only one to two values at most. The Na.values line indicates the number of missing values for each variable. The first table presents numeric data, the second, binary, and the third, other or unidentified data.
Table of General Statistics
*Check the data and make sure it reflects reality. Examine statistics and identify, if present, anomalies with statistics.
##Location of Habitat Data
###Geographical Distribution of Habitat Variables
The following graphs show the location (latitude and longitude) and the observed value for variables saved in the habitat data file.
Numeric Data
Binary Data
Binary_ENV2 <- (dplyr::select(dataset.ENV2, -Longitude, -Latitude))[which(Var_Type[match(colnames(dataset.ENV2 %>% dplyr::select(-Longitude, -Latitude)), Var_Type[,1]),2]=="Binary")]
for(i in 1:ncol(Binary_ENV2)){
graph.geo.ab <- ggplot(dataset.ENV2, aes(Longitude, Latitude)) +
geom_point(shape = 21, aes(size = (Binary_ENV2[,i]))) +
ggtitle(paste("Geographical Distribution of\n", colnames(Binary_ENV2[i]))) +
theme(plot.title = element_text(hjust = 0.5)) +
scale_size(range = c(1,10), name = "Value")
graph.geo.ab
print(graph.geo.ab)
}
## Warning: Removed 32 rows containing missing values (geom_point).
## Warning: Removed 32 rows containing missing values (geom_point).
## Warning: Removed 26 rows containing missing values (geom_point).
## Warning: Removed 23 rows containing missing values (geom_point).
## Warning: Removed 23 rows containing missing values (geom_point).
## Warning: Removed 23 rows containing missing values (geom_point).
## Warning: Removed 23 rows containing missing values (geom_point).
## Warning: Removed 23 rows containing missing values (geom_point).
rm(Binary_ENV2)
Other Data
Other_ENV2 <- (dplyr::select(dataset.ENV2, -Longitude, -Latitude, -SampleId))[which(Var_Type[match(colnames(dataset.ENV2 %>% dplyr::select(-Longitude, -Latitude, -SampleId)), Var_Type[,1]),2]!="Numeric" & Var_Type[match(colnames(dataset.ENV2 %>% dplyr::select(-Longitude, -Latitude, -SampleId)), Var_Type[,1]),2]!="Binary")]
for(i in 1:ncol(Other_ENV2)){
graph.geo.ab <- ggplot(dataset.ENV2, aes(Longitude, Latitude)) +
geom_point(shape = 21, aes(size = (Other_ENV2[,i]))) +
ggtitle(paste("Geographical Distribution of\n", colnames(Other_ENV2[i]))) +
theme(plot.title = element_text(hjust = 0.5)) +
scale_size(range = c(1,10), name = "Value")
graph.geo.ab
print(graph.geo.ab)
}
## Warning: Removed 17 rows containing missing values (geom_point).
## Warning: Removed 55 rows containing missing values (geom_point).
## Warning: Removed 289 rows containing missing values (geom_point).
## Warning: Removed 46 rows containing missing values (geom_point).
## Warning: Removed 25 rows containing missing values (geom_point).
## Warning: Removed 25 rows containing missing values (geom_point).
## Warning: Removed 25 rows containing missing values (geom_point).
## Warning: Removed 27 rows containing missing values (geom_point).
## Warning: Removed 29 rows containing missing values (geom_point).
## Warning: Removed 457 rows containing missing values (geom_point).
rm(Other_ENV2)
###Map of Altitude
The following interactive map shows an the distribution of altitude. Click on a label for more info.
## Warning in validateCoords(lng, lat, funcName): Data contains 7 rows with
## either missing or invalid lat/lon values and will be ignored
##Presence of Outliers
###Dispersion of Observed Values
The following scatterplots present the value of the continuous variable data observed in the dataset. Below the x-axis is the visit identifier for the corresponding observed value, namely the name of the site from which the data originated, its sampling date and the sampling number.
Check the data and make sure it reflects reality. Consider the following:
- Do data seem out of the ordinary?
###Boxplots of Observed and Transformed Values
The first boxplot (left) shows the distribution of continuous variable values observed in the data file, and the second box plot (right) shows the distribution of the logarithmic-transformed values.
Check the data and make sure it reflects reality. Consider the following:
- Do data seem out of the ordinary?
###Identification of Potential Outliers
For each variable, the first boxplot (left) shows the distribution of continuous variable values observed in the dataset and the dispersion diagram (right) show the distribution of observed continuous variable values in the order in which they appear in this file. Data with identification by their identifier on the diagrams are potentially outliers contained in the dataset. The method used to identify potentially outliers is the interquantile range (IQR). The IQR is calculated as follows:
IQR(x) = quantile(x, 3/4) - quantile(x, 1/4)
Potential outliers are defined as values below Q1 - 1,5 IQR or above Q3 + 1,5 IQR.
The identifier of the visit corresponds to the name of the site from which the data originated, its sampling date and the sample number for this visit.
Check the following graphs and put your attention on the points with a label (if present). Consider the following:
- Are potential outliers truly aberrant?
The following list shows another way of identifying potential outliers contained in the data file for each variable. When the identifier of a data item is indicated therein, this indicates that this data represents potentially aberrant data contained in the data file. "" indicates non-aberrant data and NA indicates missing values. The identifier of the visit corresponds to the name of the site from which the data originated, its sampling date and the sampling number.
## Altitude
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## DistanceFromSource
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Depth.Avg
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Depth.BankfullMinusWetted
## Site, Date and Number, NA
## DE06092 _ 2008-09-29 _ 17413, No
## Number of Potential Outliers: 1
##
## Depth.Max
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Discharge
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Macrophyte
## Site, Date and Number, NA
## KR09023 _ 2008-09-28 _ 18677, No
## Number of Potential Outliers: 1
##
## Reach.CanopyCoverage
## Site, Date and Number, NA
## AA06223 _ 2008-09-28 _ 17217, No
## TD10172 _ 2008-09-29 _ 16915, No
## Number of Potential Outliers: 2
##
## Reach.Logging
## Site, Date and Number, NA
## BY09291 _ 2008-09-30 _ 26231, No
## Number of Potential Outliers: 1
##
## Slope
## Site, Date and Number, NA
## CLD01 _ 2008-09-30 _ 19104, No
## VE03053 _ 2008-09-28 _ 21977, No
## Number of Potential Outliers: 2
##
## Velocity.Avg
## Site, Date and Number, NA
## AR092808 _ 2008-09-28 _ 19971, No
## ER07013 _ 2008-09-28 _ 18904, No
## Number of Potential Outliers: 2
##
## Velocity.Max
## Site, Date and Number, NA
## AR092808 _ 2008-09-28 _ 19971, No
## ER07013 _ 2008-09-28 _ 18904, No
## Number of Potential Outliers: 2
##
## Width.Bankfull
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Width.Wetted
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## XSEC.VelEquationSlope
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## XSEC.VeloEquationIntercept
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Rainfall01_JAN
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Rainfall06_JUN
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Snowfall06_JUN
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## SnowfallTotal_ANNUAL
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Temp01_JANMax
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Lake
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Drainage.Area
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## StreamDensity
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reg.Alpine
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reg.Forest
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reg.Lake
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reg.UnregenForest
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reg.Wetland
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Al
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## As
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## B
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Mg
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Ni
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Bedrock
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Boulder
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Cobble
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Gravel
## Site, Date and Number, NA
## FRS01 _ 2008-09-29 _ 19103, No
## Number of Potential Outliers: 1
##
## Pebble
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Sand
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Silt.Clay
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## D50
## Site, Date and Number, NA
## CM10303 _ 2008-09-28 _ 16919, No
## CT11043 _ 2008-09-28 _ 16854, No
## KC10083 _ 2008-09-28 _ 16911, No
## KL08313 _ 2008-09-28 _ 16868, No
## KV12193 _ 2008-09-28 _ 16832, No
## MH02263 _ 2008-09-28 _ 16859, No
## ML05023 _ 2008-09-28 _ 16900, No
## ps11143 _ 2008-09-28 _ 16844, No
## RB03093 _ 2008-09-28 _ 16845, No
## RG09063 _ 2008-09-28 _ 16862, No
## SP12243 _ 2008-09-28 _ 16838, No
## Number of Potential Outliers: 11
##
## Dg
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## SlopeAvg
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Ag
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Ba
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## CO3
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.Alkalinity
## Site, Date and Number, NA
## MG09031 _ 2012-12-12 _ 21909, No
## Number of Potential Outliers: 1
##
## General.CarbonDOC
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.Conductivity
## Site, Date and Number, NA
## AC09202 _ 2008-09-29 _ 18548, No
## Number of Potential Outliers: 1
##
## General.DO
## Site, Date and Number, NA
## SG11141 _ 2008-09-30 _ 18937, No
## Number of Potential Outliers: 1
##
## General.pH
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.SolidsTDS
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.SolidsTSS
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.SpCond
## Site, Date and Number, NA
## KM07121 _ 2008-09-30 _ 18520, No
## MH02262 _ 2008-09-29 _ 16858, No
## Number of Potential Outliers: 2
##
## General.TempAir
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.TempWater
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.Turbidity
## Site, Date and Number, NA
## AR09292 _ 2008-09-29 _ 18632, No
## BH12262 _ 2008-09-29 _ 20303, No
## CD10142 _ 2008-09-29 _ 17568, No
## CH04192 _ 2008-09-29 _ 17456, No
## CJ9272 _ 2008-09-29 _ 18748, No
## GL05232 _ 2008-09-29 _ 19073, No
## JC051402 _ 2008-09-29 _ 18777, No
## JD10192 _ 2008-09-29 _ 18829, No
## JS11112 _ 2008-09-29 _ 18479, No
## MC12282 _ 2008-09-29 _ 28316, No
## MG12282 _ 2008-09-29 _ 19090, No
## MH02262 _ 2008-09-29 _ 16858, No
## NY01031 _ 2008-09-30 _ 18781, No
## NY01032 _ 2008-09-29 _ 18850, No
## RC06232 _ 2008-09-29 _ 17481, No
## RG09062 _ 2008-09-29 _ 16861, No
## RR06232 _ 2008-09-29 _ 17572, No
## sb03292 _ 2008-09-29 _ 17132, No
## SM03262 _ 2008-09-29 _ 19074, No
## Number of Potential Outliers: 19
##
## Nitrogen.NH3
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Nitrogen.NO2
## Site, Date and Number, NA
## AB02061 _ 2008-09-30 _ 18493, No
## AB05291 _ 2008-09-30 _ 18758, No
## AP04181 _ 2008-09-30 _ 18328, No
## AS09051 _ 2008-09-30 _ 18628, No
## BS07281 _ 2008-09-30 _ 18796, No
## BT11071 _ 2008-09-30 _ 19070, No
## CS08313 _ 2008-09-28 _ 18299, No
## DJ0906101 _ 2008-09-30 _ 18545, No
## DW01311 _ 2008-09-30 _ 18821, No
## ER07011 _ 2008-09-30 _ 18901, No
## EW03271 _ 2008-09-30 _ 18331, No
## GL05231 _ 2008-09-30 _ 19069, No
## JD10191 _ 2008-09-30 _ 18828, No
## JM04621 _ 2008-09-30 _ 18923, No
## JR03271 _ 2008-09-30 _ 28210, No
## JR03272 _ 2008-09-29 _ 28212, No
## JS10011 _ 2008-09-30 _ 19075, No
## KC12141 _ 2008-09-30 _ 18661, No
## KM03021 _ 2008-09-30 _ 18655, No
## km07063 _ 2008-09-28 _ 18769, No
## KR09021 _ 2008-09-30 _ 18644, No
## LN03172 _ 2008-09-29 _ 18522, No
## LR01081 _ 2008-09-30 _ 18647, No
## LS10231 _ 2008-09-30 _ 18476, No
## MC12281 _ 2008-09-30 _ 28315, No
## MC12282 _ 2008-09-29 _ 28316, No
## MG12281 _ 2008-09-30 _ 19089, No
## ML04041 _ 2008-09-30 _ 19101, No
## NY01031 _ 2008-09-30 _ 18781, No
## PD03181 _ 2008-09-30 _ 18994, No
## PJ05151 _ 2008-09-30 _ 18516, No
## SAD01172 _ 2008-09-29 _ 19067, No
## VE03051 _ 2008-09-30 _ 21950, No
## Number of Potential Outliers: 33
##
## Nitrogen.NO2.NO3
## Site, Date and Number, NA
## BH12262 _ 2008-09-29 _ 20303, No
## km07061 _ 2008-09-30 _ 18763, No
## km07062 _ 2008-09-29 _ 18768, No
## SG11143 _ 2008-09-28 _ 18939, No
## Number of Potential Outliers: 4
##
## Nitrogen.NO3
## Site, Date and Number, NA
## CS08313 _ 2008-09-28 _ 18299, No
## Number of Potential Outliers: 1
##
## Nitrogen.TDN
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Nitrogen.TN
## Site, Date and Number, NA
## JR12092 _ 2008-09-29 _ 29506, No
## km07062 _ 2008-09-29 _ 18768, No
## km07063 _ 2008-09-28 _ 18769, No
## MR08102 _ 2008-09-29 _ 20307, No
## Number of Potential Outliers: 4
##
## Nitrogen.TN_Organic
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Phosphorus.OrthoP
## Site, Date and Number, NA
## km07062 _ 2008-09-29 _ 18768, No
## km07063 _ 2008-09-28 _ 18769, No
## Number of Potential Outliers: 2
##
## Phosphorus.TDP
## Site, Date and Number, NA
## km07061 _ 2008-09-30 _ 18763, No
## kw01012 _ 2008-09-29 _ 18844, No
## Number of Potential Outliers: 2
##
## Phosphorus.TP
## Site, Date and Number, NA
## km07062 _ 2008-09-29 _ 18768, No
## km07063 _ 2008-09-28 _ 18769, No
## MG09031 _ 2012-12-12 _ 21909, No
## Number of Potential Outliers: 3
##
## S
## Site, Date and Number, NA
## Number of Potential Outliers: 0
## Reach.Pools
## Site, Date and Number, NA
## AJ08033 _ 2008-09-28 _ 16966, No
## AKN04263 _ 2008-09-28 _ 17365, No
## AMI05223 _ 2008-09-28 _ 17494, No
## AS09193 _ 2008-09-28 _ 17498, No
## BW10113 _ 2008-09-28 _ 17253, No
## CD01233 _ 2008-09-28 _ 17274, No
## CD10143 _ 2008-09-28 _ 17573, No
## CD10163 _ 2008-09-28 _ 17438, No
## CH04193 _ 2008-09-28 _ 17461, No
## CM10303 _ 2008-09-28 _ 16919, No
## CO04143 _ 2008-09-28 _ 16923, No
## CT11043 _ 2008-09-28 _ 16854, No
## DE06093 _ 2008-09-28 _ 17418, No
## DS06123 _ 2008-09-28 _ 17570, No
## JB09273 _ 2008-09-28 _ 17477, No
## JD03233 _ 2008-09-28 _ 17466, No
## JL02063 _ 2008-09-28 _ 17578, No
## JR02123 _ 2008-09-28 _ 16936, No
## KC10083 _ 2008-09-28 _ 16911, No
## KL08313 _ 2008-09-28 _ 16868, No
## KM1223 _ 2008-09-28 _ 17489, No
## KR04193 _ 2008-09-28 _ 16967, No
## KV12193 _ 2008-09-28 _ 16832, No
## MH02263 _ 2008-09-28 _ 16859, No
## MH06143 _ 2008-09-28 _ 17597, No
## ML05023 _ 2008-09-28 _ 16900, No
## ml12223 _ 2008-09-28 _ 16992, No
## ps11143 _ 2008-09-28 _ 16844, No
## PV02043 _ 2008-09-28 _ 17478, No
## RB03093 _ 2008-09-28 _ 16845, No
## RC06233 _ 2008-09-28 _ 17482, No
## RG09063 _ 2008-09-28 _ 16862, No
## RR06233 _ 2008-09-28 _ 17574, No
## sb03293 _ 2008-09-28 _ 17133, No
## SNE06043 _ 2008-09-28 _ 16929, No
## SP12243 _ 2008-09-28 _ 16838, No
## SS05303 _ 2008-09-28 _ 16926, No
## SS11173 _ 2008-09-28 _ 17394, No
## TD10173 _ 2008-09-28 _ 16916, No
## Number of Potential Outliers: 39
##
## Reach.Rapids
## Site, Date and Number, NA
## km07062 _ 2008-09-29 _ 18768, No
## Number of Potential Outliers: 1
##
## Reach.Riffles
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reach.StraightRun
## Site, Date and Number, NA
## DJ0906101 _ 2008-09-30 _ 18545, No
## km07062 _ 2008-09-29 _ 18768, No
## ML05023 _ 2008-09-28 _ 16900, No
## MR08103 _ 2008-09-28 _ 20308, No
## Muskwa 406 _ 2011-08-05 _ 18604, No
## Muskwa 423 _ 2011-08-05 _ 18605, No
## Muskwa 424 _ 2011-08-05 _ 18606, No
## Muskwa 425 _ 2011-08-05 _ 18607, No
## Muskwa1 _ 2011-08-04 _ 18602, No
## Number of Potential Outliers: 9
##
## Veg.Coniferous
## Site, Date and Number, NA
## Muskwa 406 _ 2011-08-05 _ 18604, No
## Muskwa 423 _ 2011-08-05 _ 18605, No
## Muskwa 424 _ 2011-08-05 _ 18606, No
## Muskwa 425 _ 2011-08-05 _ 18607, No
## Muskwa1 _ 2011-08-04 _ 18602, No
## NY01032 _ 2008-09-29 _ 18850, No
## RC06232 _ 2008-09-29 _ 17481, No
## Number of Potential Outliers: 7
##
## Veg.Deciduous
## Site, Date and Number, NA
## Muskwa 406 _ 2011-08-05 _ 18604, No
## Muskwa 423 _ 2011-08-05 _ 18605, No
## Muskwa 424 _ 2011-08-05 _ 18606, No
## Muskwa 425 _ 2011-08-05 _ 18607, No
## Muskwa1 _ 2011-08-04 _ 18602, No
## NY01032 _ 2008-09-29 _ 18850, No
## Number of Potential Outliers: 6
##
## Veg.GrassesFerns
## Site, Date and Number, NA
## Muskwa 406 _ 2011-08-05 _ 18604, No
## Muskwa 423 _ 2011-08-05 _ 18605, No
## Muskwa 424 _ 2011-08-05 _ 18606, No
## Muskwa 425 _ 2011-08-05 _ 18607, No
## Muskwa1 _ 2011-08-04 _ 18602, No
## RC06232 _ 2008-09-29 _ 17481, No
## Number of Potential Outliers: 6
##
## Veg.Shrubs
## Site, Date and Number, NA
## Muskwa 406 _ 2011-08-05 _ 18604, No
## Muskwa 423 _ 2011-08-05 _ 18605, No
## Muskwa 424 _ 2011-08-05 _ 18606, No
## Muskwa 425 _ 2011-08-05 _ 18607, No
## Muskwa1 _ 2011-08-04 _ 18602, No
## NY01032 _ 2008-09-29 _ 18850, No
## RC06232 _ 2008-09-29 _ 17481, No
## Number of Potential Outliers: 7
## StreamOrder
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Reach.DomStreamsideVeg
## Site, Date and Number, NA
## RB03091 _ 2008-09-30 _ 16841, No
## Number of Potential Outliers: 1
##
## XSEC.VelInstrumentDirect
## Site, Date and Number, NA
## AA06223 _ 2008-09-28 _ 17217, No
## AJ08033 _ 2008-09-28 _ 16966, No
## AKN04263 _ 2008-09-28 _ 17365, No
## AMI05223 _ 2008-09-28 _ 17494, No
## AS09193 _ 2008-09-28 _ 17498, No
## BW10113 _ 2008-09-28 _ 17253, No
## CD01233 _ 2008-09-28 _ 17274, No
## CD10143 _ 2008-09-28 _ 17573, No
## CH04193 _ 2008-09-28 _ 17461, No
## CM10303 _ 2008-09-28 _ 16919, No
## CO04143 _ 2008-09-28 _ 16923, No
## CT11043 _ 2008-09-28 _ 16854, No
## DE06093 _ 2008-09-28 _ 17418, No
## DS06123 _ 2008-09-28 _ 17570, No
## JB09273 _ 2008-09-28 _ 17477, No
## JD03233 _ 2008-09-28 _ 17466, No
## JL02063 _ 2008-09-28 _ 17578, No
## JR02123 _ 2008-09-28 _ 16936, No
## KC10083 _ 2008-09-28 _ 16911, No
## KL08313 _ 2008-09-28 _ 16868, No
## KM1221 _ 2008-09-30 _ 17483, No
## KM1223 _ 2008-09-28 _ 17489, No
## KR04193 _ 2008-09-28 _ 16967, No
## KV12193 _ 2008-09-28 _ 16832, No
## MH02263 _ 2008-09-28 _ 16859, No
## MH06143 _ 2008-09-28 _ 17597, No
## ML05023 _ 2008-09-28 _ 16900, No
## ml12223 _ 2008-09-28 _ 16992, No
## ps11143 _ 2008-09-28 _ 16844, No
## PV02043 _ 2008-09-28 _ 17478, No
## RB03093 _ 2008-09-28 _ 16845, No
## RC06233 _ 2008-09-28 _ 17482, No
## RG09063 _ 2008-09-28 _ 16862, No
## RR06233 _ 2008-09-28 _ 17574, No
## sb03293 _ 2008-09-28 _ 17133, No
## SNE06043 _ 2008-09-28 _ 16929, No
## SP12243 _ 2008-09-28 _ 16838, No
## SS05303 _ 2008-09-28 _ 16926, No
## SS11173 _ 2008-09-28 _ 17394, No
## TD10173 _ 2008-09-28 _ 16916, No
## Number of Potential Outliers: 40
##
## XSEC.VelMethod
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Dominant.1st
## Site, Date and Number, NA
## FRS01 _ 2008-09-29 _ 19103, No
## Number of Potential Outliers: 1
##
## Dominant.2nd
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## Embeddedness
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## PeriphytonCoverage
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## SurroundingMaterial
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##
## General.Colour
## Site, Date and Number, NA
## Number of Potential Outliers: 0
##Data Normality
###Quantile-Quantile Diagrams and Frequency Histograms
For each variable, the first graph (left) shows the observed distribution of variable values by points and the theoretical normal distribution calculated from the parameters of the distribution observed by a straight line. The more the observed values are positioned along the line, the more they are distributed according to the normality.
The second graph (middle) illustrates a frequency histogram of the observed values taxon. This histogram also shows the average value per variable by a solid line and the standard deviation of the two variables by dotted lines.
The third graph (right) illustrates the frequency distribution of the observed values per variable that are log-transformed. If the distribution of the data on this graph seems to be more like a normal distribution, a logarithmic transformation of the data might be useful. This histogram also illustrates the average value per variable by a solid line as well as the standard deviation of the variables by two dashed lines.
###Boxplots of Observed Values
For each variable, the first boxplot (left) shows the distribution of observed values in the data file whereas the second boxplot (right) shows the distribution of observed values in the data file that has undergone logarithmic transformation.
###Normality Tests
Les résultats suivants présentent le résultat obtenu par un test de Snows appliqué sur chaque variable du fichier de données. Une valeur de P (p-value) inférieure à 0.05 indique qu’il n’est pas possible de supposer que la distribution des données suit la loi normale avec une probabilité de 95%.
## $SampleId
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Altitude
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $DistanceFromSource
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Depth.Avg
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Depth.BankfullMinusWetted
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Depth.Max
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Discharge
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Macrophyte
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.CanopyCoverage
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.Logging
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Slope
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Velocity.Avg
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Velocity.Max
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Width.Bankfull
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Width.Wetted
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $XSEC.VelEquationSlope
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $XSEC.VeloEquationIntercept
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Rainfall01_JAN
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Rainfall06_JUN
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Snowfall06_JUN
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $SnowfallTotal_ANNUAL
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Temp01_JANMax
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Lake
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Drainage.Area
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $StreamDensity
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reg.Alpine
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reg.Forest
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reg.Lake
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reg.UnregenForest
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reg.Wetland
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Al
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $As
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $B
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Mg
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Ni
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Bedrock
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Boulder
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Cobble
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Gravel
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Pebble
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Sand
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Silt.Clay
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $D50
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Dg
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $SlopeAvg
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Ag
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Ba
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $CO3
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.Alkalinity
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.CarbonDOC
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.Conductivity
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.DO
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.pH
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.SolidsTDS
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.SolidsTSS
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.SpCond
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.TempAir
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.TempWater
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.Turbidity
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.NH3
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.NO2
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.NO2.NO3
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.NO3
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.TDN
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.TN
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Nitrogen.TN_Organic
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Phosphorus.OrthoP
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Phosphorus.TDP
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Phosphorus.TP
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $S
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Site_Date_Number
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
## $SampleId
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.Pools
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.Rapids
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.Riffles
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.StraightRun
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Veg.Coniferous
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Veg.Deciduous
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Veg.GrassesFerns
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Veg.Shrubs
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Site_Date_Number
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
## $SampleId
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $StreamOrder
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Reach.DomStreamsideVeg
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $XSEC.VelInstrumentDirect
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $XSEC.VelMethod
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Dominant.1st
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Dominant.2nd
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Embeddedness
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $PeriphytonCoverage
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $SurroundingMaterial
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $General.Colour
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##
##
## $Site_Date_Number
##
## Snow's Penultimate Normality Test
##
## data: newX[, i]
## p-value < 2.2e-16
## alternative hypothesis:
## The data does not come from a strict normal distribution (but
## may represent a distribution that is close enough)
##Collinearity of Variables
###Scatterplot Matrix
The following scatterplot matrix illustrates the relationship between pairs of variables. It helps to detect the presence of correlations between variables.
## [1] 20
## plot: [1,1] [---------------------------------------------] 0% est:
## 0s plot: [1,2] [---------------------------------------------] 0% est:
## 23s plot: [1,3] [---------------------------------------------] 1% est:
## 26s plot: [1,4] [---------------------------------------------] 1% est:
## 28s plot: [1,5] [>--------------------------------------------] 1% est:
## 29s plot: [1,6] [>--------------------------------------------] 2% est:
## 29s plot: [1,7] [>--------------------------------------------] 2% est:
## 30s plot: [1,8] [>--------------------------------------------] 2% est:
## 30s plot: [1,9] [>--------------------------------------------] 2% est:
## 31s plot: [1,10] [>-------------------------------------------] 2% est:
## 31s plot: [1,11] [>-------------------------------------------] 3% est:
## 31s plot: [1,12] [>-------------------------------------------] 3% est:
## 31s plot: [1,13] [>-------------------------------------------] 3% est:
## 31s plot: [1,14] [=>------------------------------------------] 4% est:
## 31s plot: [1,15] [=>------------------------------------------] 4% est:
## 31s plot: [1,16] [=>------------------------------------------] 4% est:31s
## plot: [1,17] [=>------------------------------------------] 4% est:31s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [1,18] [=>------------------------------------------] 4% est:
## 32s plot: [1,19] [=>------------------------------------------] 5% est:
## 32s plot: [1,20] [=>------------------------------------------] 5% est:
## 32s plot: [2,1] [=>-------------------------------------------] 5% est:
## 32s plot: [2,2] [=>-------------------------------------------] 6% est:
## 32s plot: [2,3] [==>------------------------------------------] 6% est:
## 32s plot: [2,4] [==>------------------------------------------] 6% est:
## 32s plot: [2,5] [==>------------------------------------------] 6% est:
## 32s plot: [2,6] [==>------------------------------------------] 6% est:
## 32s plot: [2,7] [==>------------------------------------------] 7% est:
## 32s plot: [2,8] [==>------------------------------------------] 7% est:
## 33s plot: [2,9] [==>------------------------------------------] 7% est:
## 32s plot: [2,10] [==>-----------------------------------------] 8% est:
## 32s plot: [2,11] [==>-----------------------------------------] 8% est:
## 32s plot: [2,12] [===>----------------------------------------] 8% est:
## 32s plot: [2,13] [===>----------------------------------------] 8% est:
## 32s plot: [2,14] [===>----------------------------------------] 8% est:
## 32s plot: [2,15] [===>----------------------------------------] 9% est:
## 32s plot: [2,16] [===>----------------------------------------] 9% est:32s
## plot: [2,17] [===>----------------------------------------] 9% est:32s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [2,18] [===>----------------------------------------] 10% est:
## 32s plot: [2,19] [===>----------------------------------------] 10% est:
## 32s plot: [2,20] [===>----------------------------------------] 10% est:
## 32s plot: [3,1] [====>----------------------------------------] 10% est:
## 31s plot: [3,2] [====>----------------------------------------] 10% est:
## 31s plot: [3,3] [====>----------------------------------------] 11% est:
## 31s plot: [3,4] [====>----------------------------------------] 11% est:
## 31s plot: [3,5] [====>----------------------------------------] 11% est:
## 32s plot: [3,6] [====>----------------------------------------] 12% est:
## 32s plot: [3,7] [====>----------------------------------------] 12% est:
## 32s plot: [3,8] [====>----------------------------------------] 12% est:
## 32s plot: [3,9] [=====>---------------------------------------] 12% est:
## 32s plot: [3,10] [=====>--------------------------------------] 12% est:
## 31s plot: [3,11] [=====>--------------------------------------] 13% est:
## 31s plot: [3,12] [=====>--------------------------------------] 13% est:
## 31s plot: [3,13] [=====>--------------------------------------] 13% est:
## 31s plot: [3,14] [=====>--------------------------------------] 14% est:
## 31s plot: [3,15] [=====>--------------------------------------] 14% est:
## 31s plot: [3,16] [=====>--------------------------------------] 14% est:31s
## plot: [3,17] [=====>--------------------------------------] 14% est:31s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [3,18] [=====>--------------------------------------] 14% est:
## 31s plot: [3,19] [=====>--------------------------------------] 15% est:
## 31s plot: [3,20] [======>-------------------------------------] 15% est:
## 31s plot: [4,1] [======>--------------------------------------] 15% est:
## 31s plot: [4,2] [======>--------------------------------------] 16% est:
## 31s plot: [4,3] [======>--------------------------------------] 16% est:
## 30s plot: [4,4] [======>--------------------------------------] 16% est:
## 30s plot: [4,5] [======>--------------------------------------] 16% est:
## 30s plot: [4,6] [======>--------------------------------------] 16% est:
## 30s plot: [4,7] [=======>-------------------------------------] 17% est:
## 30s plot: [4,8] [=======>-------------------------------------] 17% est:
## 30s plot: [4,9] [=======>-------------------------------------] 17% est:
## 30s plot: [4,10] [=======>------------------------------------] 18% est:
## 30s plot: [4,11] [=======>------------------------------------] 18% est:
## 30s plot: [4,12] [=======>------------------------------------] 18% est:
## 30s plot: [4,13] [=======>------------------------------------] 18% est:
## 30s plot: [4,14] [=======>------------------------------------] 18% est:
## 30s plot: [4,15] [=======>------------------------------------] 19% est:
## 29s plot: [4,16] [=======>------------------------------------] 19% est:29s
## plot: [4,17] [=======>------------------------------------] 19% est:29s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [4,18] [========>-----------------------------------] 20% est:
## 29s plot: [4,19] [========>-----------------------------------] 20% est:
## 29s plot: [4,20] [========>-----------------------------------] 20% est:
## 29s plot: [5,1] [========>------------------------------------] 20% est:
## 29s plot: [5,2] [========>------------------------------------] 20% est:
## 29s plot: [5,3] [========>------------------------------------] 21% est:
## 29s plot: [5,4] [========>------------------------------------] 21% est:
## 29s plot: [5,5] [=========>-----------------------------------] 21% est:
## 29s plot: [5,6] [=========>-----------------------------------] 22% est:
## 29s plot: [5,7] [=========>-----------------------------------] 22% est:
## 28s plot: [5,8] [=========>-----------------------------------] 22% est:
## 28s plot: [5,9] [=========>-----------------------------------] 22% est:
## 28s plot: [5,10] [=========>----------------------------------] 22% est:
## 28s plot: [5,11] [=========>----------------------------------] 23% est:
## 28s plot: [5,12] [=========>----------------------------------] 23% est:
## 28s plot: [5,13] [=========>----------------------------------] 23% est:
## 28s plot: [5,14] [=========>----------------------------------] 24% est:
## 28s plot: [5,15] [=========>----------------------------------] 24% est:
## 28s plot: [5,16] [==========>---------------------------------] 24% est:28s
## plot: [5,17] [==========>---------------------------------] 24% est:28s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [5,18] [==========>---------------------------------] 24% est:
## 28s plot: [5,19] [==========>---------------------------------] 25% est:
## 28s plot: [5,20] [==========>---------------------------------] 25% est:
## 28s plot: [6,1] [==========>----------------------------------] 25% est:
## 28s plot: [6,2] [==========>----------------------------------] 26% est:
## 27s plot: [6,3] [===========>---------------------------------] 26% est:
## 27s plot: [6,4] [===========>---------------------------------] 26% est:
## 27s plot: [6,5] [===========>---------------------------------] 26% est:
## 27s plot: [6,6] [===========>---------------------------------] 26% est:
## 27s plot: [6,7] [===========>---------------------------------] 27% est:
## 28s plot: [6,8] [===========>---------------------------------] 27% est:
## 28s plot: [6,9] [===========>---------------------------------] 27% est:
## 28s plot: [6,10] [===========>--------------------------------] 28% est:
## 28s plot: [6,11] [===========>--------------------------------] 28% est:
## 28s plot: [6,12] [===========>--------------------------------] 28% est:
## 28s plot: [6,13] [===========>--------------------------------] 28% est:
## 28s plot: [6,14] [============>-------------------------------] 28% est:
## 28s plot: [6,15] [============>-------------------------------] 29% est:
## 27s plot: [6,16] [============>-------------------------------] 29% est:28s
## plot: [6,17] [============>-------------------------------] 29% est:27s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [6,18] [============>-------------------------------] 30% est:
## 27s plot: [6,19] [============>-------------------------------] 30% est:
## 27s plot: [6,20] [============>-------------------------------] 30% est:
## 27s plot: [7,1] [=============>-------------------------------] 30% est:
## 27s plot: [7,2] [=============>-------------------------------] 30% est:
## 27s plot: [7,3] [=============>-------------------------------] 31% est:
## 27s plot: [7,4] [=============>-------------------------------] 31% est:
## 27s plot: [7,5] [=============>-------------------------------] 31% est:
## 27s plot: [7,6] [=============>-------------------------------] 32% est:
## 27s plot: [7,7] [=============>-------------------------------] 32% est:
## 27s plot: [7,8] [=============>-------------------------------] 32% est:
## 27s plot: [7,9] [==============>------------------------------] 32% est:
## 27s plot: [7,10] [=============>------------------------------] 32% est:
## 27s plot: [7,11] [=============>------------------------------] 33% est:
## 27s plot: [7,12] [==============>-----------------------------] 33% est:
## 27s plot: [7,13] [==============>-----------------------------] 33% est:
## 27s plot: [7,14] [==============>-----------------------------] 34% est:
## 27s plot: [7,15] [==============>-----------------------------] 34% est:
## 26s plot: [7,16] [==============>-----------------------------] 34% est:26s
## plot: [7,17] [==============>-----------------------------] 34% est:26s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [7,18] [==============>-----------------------------] 34% est:
## 26s plot: [7,19] [==============>-----------------------------] 35% est:
## 26s plot: [7,20] [==============>-----------------------------] 35% est:
## 26s plot: [8,1] [===============>-----------------------------] 35% est:
## 26s plot: [8,2] [===============>-----------------------------] 36% est:
## 26s plot: [8,3] [===============>-----------------------------] 36% est:
## 26s plot: [8,4] [===============>-----------------------------] 36% est:
## 26s plot: [8,5] [===============>-----------------------------] 36% est:
## 26s plot: [8,6] [===============>-----------------------------] 36% est:
## 26s plot: [8,7] [================>----------------------------] 37% est:
## 25s plot: [8,8] [================>----------------------------] 37% est:
## 25s plot: [8,9] [================>----------------------------] 37% est:
## 25s plot: [8,10] [===============>----------------------------] 38% est:
## 25s plot: [8,11] [================>---------------------------] 38% est:
## 25s plot: [8,12] [================>---------------------------] 38% est:
## 25s plot: [8,13] [================>---------------------------] 38% est:
## 25s plot: [8,14] [================>---------------------------] 38% est:
## 25s plot: [8,15] [================>---------------------------] 39% est:
## 25s plot: [8,16] [================>---------------------------] 39% est:25s
## plot: [8,17] [================>---------------------------] 39% est:25s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [8,18] [================>---------------------------] 40% est:
## 25s plot: [8,19] [================>---------------------------] 40% est:
## 25s plot: [8,20] [=================>--------------------------] 40% est:
## 25s plot: [9,1] [=================>---------------------------] 40% est:
## 25s plot: [9,2] [=================>---------------------------] 40% est:
## 24s plot: [9,3] [=================>---------------------------] 41% est:
## 24s plot: [9,4] [=================>---------------------------] 41% est:
## 24s plot: [9,5] [==================>--------------------------] 41% est:
## 24s plot: [9,6] [==================>--------------------------] 42% est:
## 24s plot: [9,7] [==================>--------------------------] 42% est:
## 24s plot: [9,8] [==================>--------------------------] 42% est:
## 24s plot: [9,9] [==================>--------------------------] 42% est:
## 24s plot: [9,10] [==================>-------------------------] 42% est:
## 24s plot: [9,11] [==================>-------------------------] 43% est:
## 24s plot: [9,12] [==================>-------------------------] 43% est:
## 24s plot: [9,13] [==================>-------------------------] 43% est:
## 23s plot: [9,14] [==================>-------------------------] 44% est:
## 23s plot: [9,15] [==================>-------------------------] 44% est:
## 23s plot: [9,16] [==================>-------------------------] 44% est:23s
## plot: [9,17] [==================>-------------------------] 44% est:23s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [9,18] [===================>------------------------] 44% est:
## 23s plot: [9,19] [===================>------------------------] 45% est:
## 23s plot: [9,20] [===================>------------------------] 45% est:
## 23s plot: [10,1] [===================>------------------------] 45% est:
## 22s plot: [10,2] [===================>------------------------] 46% est:
## 22s plot: [10,3] [===================>------------------------] 46% est:
## 22s plot: [10,4] [===================>------------------------] 46% est:
## 22s plot: [10,5] [===================>------------------------] 46% est:
## 22s plot: [10,6] [===================>------------------------] 46% est:
## 22s plot: [10,7] [====================>-----------------------] 47% est:
## 22s plot: [10,8] [====================>-----------------------] 47% est:
## 22s plot: [10,9] [====================>-----------------------] 47% est:
## 22s plot: [10,10] [===================>-----------------------] 48% est:
## 22s plot: [10,11] [====================>----------------------] 48% est:
## 21s plot: [10,12] [====================>----------------------] 48% est:
## 21s plot: [10,13] [====================>----------------------] 48% est:
## 21s plot: [10,14] [====================>----------------------] 48% est:
## 21s plot: [10,15] [====================>----------------------] 49% est:
## 21s plot: [10,16] [====================>----------------------] 49% est:21s
## plot: [10,17] [====================>----------------------] 49% est:21s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [10,18] [====================>----------------------] 50% est:
## 21s plot: [10,19] [====================>----------------------] 50% est:
## 21s plot: [10,20] [=====================>---------------------] 50% est:
## 21s plot: [11,1] [=====================>----------------------] 50% est:
## 20s plot: [11,2] [=====================>----------------------] 50% est:
## 20s plot: [11,3] [=====================>----------------------] 51% est:
## 20s plot: [11,4] [=====================>----------------------] 51% est:
## 20s plot: [11,5] [======================>---------------------] 51% est:
## 20s plot: [11,6] [======================>---------------------] 52% est:
## 20s plot: [11,7] [======================>---------------------] 52% est:
## 20s plot: [11,8] [======================>---------------------] 52% est:
## 20s plot: [11,9] [======================>---------------------] 52% est:
## 20s plot: [11,10] [======================>--------------------] 52% est:
## 20s plot: [11,11] [======================>--------------------] 53% est:
## 20s plot: [11,12] [======================>--------------------] 53% est:
## 20s plot: [11,13] [======================>--------------------] 53% est:
## 20s plot: [11,14] [======================>--------------------] 54% est:
## 19s plot: [11,15] [======================>--------------------] 54% est:
## 19s plot: [11,16] [======================>--------------------] 54% est:19s
## plot: [11,17] [======================>--------------------] 54% est:19s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [11,18] [======================>--------------------] 55% est:
## 19s plot: [11,19] [=======================>-------------------] 55% est:
## 19s plot: [11,20] [=======================>-------------------] 55% est:
## 19s plot: [12,1] [=======================>--------------------] 55% est:
## 19s plot: [12,2] [=======================>--------------------] 56% est:
## 19s plot: [12,3] [========================>-------------------] 56% est:
## 19s plot: [12,4] [========================>-------------------] 56% est:
## 18s plot: [12,5] [========================>-------------------] 56% est:
## 18s plot: [12,6] [========================>-------------------] 56% est:
## 18s plot: [12,7] [========================>-------------------] 57% est:
## 18s plot: [12,8] [========================>-------------------] 57% est:
## 18s plot: [12,9] [========================>-------------------] 57% est:
## 18s plot: [12,10] [========================>------------------] 57% est:
## 18s plot: [12,11] [========================>------------------] 58% est:
## 18s plot: [12,12] [========================>------------------] 58% est:
## 18s plot: [12,13] [========================>------------------] 58% est:
## 18s plot: [12,14] [========================>------------------] 58% est:
## 17s plot: [12,15] [========================>------------------] 59% est:
## 17s plot: [12,16] [========================>------------------] 59% est:17s
## plot: [12,17] [========================>------------------] 59% est:17s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [12,18] [=========================>-----------------] 60% est:
## 17s plot: [12,19] [=========================>-----------------] 60% est:
## 17s plot: [12,20] [=========================>-----------------] 60% est:
## 17s plot: [13,1] [==========================>-----------------] 60% est:
## 17s plot: [13,2] [==========================>-----------------] 60% est:
## 17s plot: [13,3] [==========================>-----------------] 61% est:
## 17s plot: [13,4] [==========================>-----------------] 61% est:
## 17s plot: [13,5] [==========================>-----------------] 61% est:
## 16s plot: [13,6] [==========================>-----------------] 62% est:
## 16s plot: [13,7] [==========================>-----------------] 62% est:
## 16s plot: [13,8] [==========================>-----------------] 62% est:
## 16s plot: [13,9] [==========================>-----------------] 62% est:
## 16s plot: [13,10] [==========================>----------------] 62% est:
## 16s plot: [13,11] [==========================>----------------] 63% est:
## 16s plot: [13,12] [==========================>----------------] 63% est:
## 16s plot: [13,13] [==========================>----------------] 63% est:
## 16s plot: [13,14] [==========================>----------------] 64% est:
## 16s plot: [13,15] [==========================>----------------] 64% est:
## 15s plot: [13,16] [===========================>---------------] 64% est:15s
## plot: [13,17] [===========================>---------------] 64% est:15s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [13,18] [===========================>---------------] 64% est:
## 15s plot: [13,19] [===========================>---------------] 65% est:
## 15s plot: [13,20] [===========================>---------------] 65% est:
## 15s plot: [14,1] [============================>---------------] 65% est:
## 15s plot: [14,2] [============================>---------------] 66% est:
## 15s plot: [14,3] [============================>---------------] 66% est:
## 15s plot: [14,4] [============================>---------------] 66% est:
## 15s plot: [14,5] [============================>---------------] 66% est:
## 15s plot: [14,6] [============================>---------------] 66% est:
## 15s plot: [14,7] [============================>---------------] 67% est:
## 15s plot: [14,8] [============================>---------------] 67% est:
## 15s plot: [14,9] [=============================>--------------] 67% est:
## 15s plot: [14,10] [============================>--------------] 68% est:
## 15s plot: [14,11] [============================>--------------] 68% est:
## 15s plot: [14,12] [============================>--------------] 68% est:
## 15s plot: [14,13] [============================>--------------] 68% est:
## 15s plot: [14,14] [============================>--------------] 68% est:
## 15s plot: [14,15] [=============================>-------------] 69% est:
## 15s plot: [14,16] [=============================>-------------] 69% est:15s
## plot: [14,17] [=============================>-------------] 69% est:15s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [14,18] [=============================>-------------] 70% est:
## 15s plot: [14,19] [=============================>-------------] 70% est:
## 14s plot: [14,20] [=============================>-------------] 70% est:
## 14s plot: [15,1] [==============================>-------------] 70% est:
## 14s plot: [15,2] [==============================>-------------] 70% est:
## 14s plot: [15,3] [==============================>-------------] 71% est:
## 14s plot: [15,4] [==============================>-------------] 71% est:
## 14s plot: [15,5] [==============================>-------------] 71% est:
## 14s plot: [15,6] [==============================>-------------] 72% est:
## 14s plot: [15,7] [===============================>------------] 72% est:
## 13s plot: [15,8] [===============================>------------] 72% est:
## 13s plot: [15,9] [===============================>------------] 72% est:
## 13s plot: [15,10] [==============================>------------] 72% est:
## 13s plot: [15,11] [==============================>------------] 73% est:
## 13s plot: [15,12] [==============================>------------] 73% est:
## 13s plot: [15,13] [==============================>------------] 73% est:
## 13s plot: [15,14] [===============================>-----------] 74% est:
## 13s plot: [15,15] [===============================>-----------] 74% est:
## 12s plot: [15,16] [===============================>-----------] 74% est:12s
## plot: [15,17] [===============================>-----------] 74% est:12s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [15,18] [===============================>-----------] 74% est:
## 12s plot: [15,19] [===============================>-----------] 75% est:
## 12s plot: [15,20] [===============================>-----------] 75% est:
## 12s plot: [16,1] [================================>-----------] 75% est:
## 12s plot: [16,2] [================================>-----------] 76% est:
## 12s plot: [16,3] [================================>-----------] 76% est:
## 11s plot: [16,4] [================================>-----------] 76% est:
## 11s plot: [16,5] [=================================>----------] 76% est:
## 11s plot: [16,6] [=================================>----------] 76% est:
## 11s plot: [16,7] [=================================>----------] 77% est:
## 11s plot: [16,8] [=================================>----------] 77% est:
## 11s plot: [16,9] [=================================>----------] 77% est:
## 11s plot: [16,10] [================================>----------] 78% est:
## 11s plot: [16,11] [================================>----------] 78% est:
## 10s plot: [16,12] [=================================>---------] 78% est:
## 10s plot: [16,13] [=================================>---------] 78% est:
## 10s plot: [16,14] [=================================>---------] 78% est:
## 10s plot: [16,15] [=================================>---------] 79% est:
## 10s plot: [16,16] [=================================>---------] 79% est:10s
## plot: [16,17] [=================================>---------] 79% est:10s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [16,18] [=================================>---------] 80% est:10s
## plot: [16,19] [=================================>---------] 80% est: 9s
## plot: [16,20] [=================================>---------] 80% est: 9s
## plot: [17,1] [==================================>---------] 80% est: 9s
## plot: [17,2] [==================================>---------] 80% est: 9s
## plot: [17,3] [===================================>--------] 81% est: 9s
## plot: [17,4] [===================================>--------] 81% est: 9s
## plot: [17,5] [===================================>--------] 81% est: 9s
## plot: [17,6] [===================================>--------] 82% est: 9s
## plot: [17,7] [===================================>--------] 82% est: 9s
## plot: [17,8] [===================================>--------] 82% est: 8s
## plot: [17,9] [===================================>--------] 82% est: 8s
## plot: [17,10] [==================================>--------] 82% est: 8s
## plot: [17,11] [===================================>-------] 83% est: 8s
## plot: [17,12] [===================================>-------] 83% est: 8s
## plot: [17,13] [===================================>-------] 83% est: 8s
## plot: [17,14] [===================================>-------] 84% est: 8s
## plot: [17,15] [===================================>-------] 84% est: 8s
## plot: [17,16] [===================================>-------] 84% est: 7s
## plot: [17,17] [===================================>-------] 84% est: 7s
## plot: [17,18] [===================================>-------] 84% est: 7s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [17,19] [===================================>-------] 85% est: 7s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [17,20] [====================================>------] 85% est: 7s
## Warning in cor(x, y, method = method, use = use): l'écart type est nulle
## plot: [18,1] [=====================================>------] 85% est: 7s
## plot: [18,2] [=====================================>------] 86% est: 7s
## plot: [18,3] [=====================================>------] 86% est: 7s
## plot: [18,4] [=====================================>------] 86% est: 6s
## plot: [18,5] [=====================================>------] 86% est: 6s
## plot: [18,6] [=====================================>------] 86% est: 6s
## plot: [18,7] [=====================================>------] 87% est: 6s
## plot: [18,8] [=====================================>------] 87% est: 6s
## plot: [18,9] [=====================================>------] 87% est: 6s
## plot: [18,10] [=====================================>-----] 88% est: 6s
## plot: [18,11] [=====================================>-----] 88% est: 6s
## plot: [18,12] [=====================================>-----] 88% est: 6s
## plot: [18,13] [=====================================>-----] 88% est: 5s
## plot: [18,14] [=====================================>-----] 88% est: 5s
## plot: [18,15] [=====================================>-----] 89% est: 5s
## plot: [18,16] [=====================================>-----] 89% est: 5s
## plot: [18,17] [=====================================>-----] 89% est: 5s
## plot: [18,18] [=====================================>-----] 90% est: 5s
## plot: [18,19] [======================================>----] 90% est: 5s
## plot: [18,20] [======================================>----] 90% est: 5s
## plot: [19,1] [=======================================>----] 90% est: 4s
## plot: [19,2] [=======================================>----] 90% est: 4s
## plot: [19,3] [=======================================>----] 91% est: 4s
## plot: [19,4] [=======================================>----] 91% est: 4s
## plot: [19,5] [=======================================>----] 91% est: 4s
## plot: [19,6] [=======================================>----] 92% est: 4s
## plot: [19,7] [=======================================>----] 92% est: 4s
## plot: [19,8] [=======================================>----] 92% est: 4s
## plot: [19,9] [========================================>---] 92% est: 4s
## plot: [19,10] [=======================================>---] 92% est: 3s
## plot: [19,11] [=======================================>---] 93% est: 3s
## plot: [19,12] [=======================================>---] 93% est: 3s
## plot: [19,13] [=======================================>---] 93% est: 3s
## plot: [19,14] [=======================================>---] 94% est: 3s
## plot: [19,15] [=======================================>---] 94% est: 3s
## plot: [19,16] [=======================================>---] 94% est: 3s
## plot: [19,17] [========================================>--] 94% est: 3s
## plot: [19,18] [========================================>--] 94% est: 3s
## plot: [19,19] [========================================>--] 95% est: 2s
## plot: [19,20] [========================================>--] 95% est: 2s
## plot: [20,1] [=========================================>--] 95% est: 2s
## plot: [20,2] [=========================================>--] 96% est: 2s
## plot: [20,3] [=========================================>--] 96% est: 2s
## plot: [20,4] [=========================================>--] 96% est: 2s
## plot: [20,5] [=========================================>--] 96% est: 2s
## plot: [20,6] [=========================================>--] 96% est: 2s
## plot: [20,7] [==========================================>-] 97% est: 1s
## plot: [20,8] [==========================================>-] 97% est: 1s
## plot: [20,9] [==========================================>-] 97% est: 1s
## plot: [20,10] [=========================================>-] 98% est: 1s
## plot: [20,11] [=========================================>-] 98% est: 1s
## plot: [20,12] [=========================================>-] 98% est: 1s
## plot: [20,13] [=========================================>-] 98% est: 1s
## plot: [20,14] [=========================================>-] 98% est: 1s
## plot: [20,15] [=========================================>-] 99% est: 1s
## plot: [20,16] [==========================================>] 99% est: 0s
## plot: [20,17] [==========================================>] 99% est: 0s
## plot: [20,18] [==========================================>]100% est: 0s
## plot: [20,19] [==========================================>]100% est: 0s
## plot: [20,20] [===========================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.005625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.075
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 227.26
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 1s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 3.404e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.001845
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.13753
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## plot: [1,3] [=======>-------------------------------------] 19% est: 2s
## plot: [1,4] [==========>----------------------------------] 25% est: 2s
## plot: [2,1] [=============>-------------------------------] 31% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 0s
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 2s
## plot: [1,3] [=======>-------------------------------------] 19% est: 2s
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## plot: [3,4] [=================================>-----------] 75% est: 1s
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## plot: [4,4] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 351.75
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 337.25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 9.9172e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.1256e+005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 351.75
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 337.25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 9.9172e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.1256e+005
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.1618e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0034085
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.46937
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.1025e-010
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.45e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 8.4943e-006
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 2s
## plot: [2,2] [================>----------------------------] 38% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.050625
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.225
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2045.3
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-007
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.0101
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.36784
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6065
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 14861
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## [1] 8
## plot: [1,1] [>--------------------------------------------] 2% est: 0s
## plot: [1,2] [>--------------------------------------------] 3% est: 4s
## plot: [1,3] [=>-------------------------------------------] 5% est: 4s
## plot: [1,4] [==>------------------------------------------] 6% est: 5s
## plot: [1,5] [===>-----------------------------------------] 8% est: 5s
## plot: [1,6] [===>-----------------------------------------] 9% est: 5s
## plot: [1,7] [====>----------------------------------------] 11% est: 5s
## plot: [1,8] [=====>---------------------------------------] 12% est: 5s
## plot: [2,1] [=====>---------------------------------------] 14% est: 5s
## plot: [2,2] [======>--------------------------------------] 16% est: 6s
## plot: [2,3] [=======>-------------------------------------] 17% est: 6s
## plot: [2,4] [=======>-------------------------------------] 19% est: 5s
## plot: [2,5] [========>------------------------------------] 20% est: 5s
## plot: [2,6] [=========>-----------------------------------] 22% est: 5s
## plot: [2,7] [==========>----------------------------------] 23% est: 5s
## plot: [2,8] [==========>----------------------------------] 25% est: 5s
## plot: [3,1] [===========>---------------------------------] 27% est: 5s
## plot: [3,2] [============>--------------------------------] 28% est: 5s
## plot: [3,3] [============>--------------------------------] 30% est: 5s
## plot: [3,4] [=============>-------------------------------] 31% est: 5s
## plot: [3,5] [==============>------------------------------] 33% est: 4s
## plot: [3,6] [==============>------------------------------] 34% est: 4s
## plot: [3,7] [===============>-----------------------------] 36% est: 4s
## plot: [3,8] [================>----------------------------] 38% est: 4s
## plot: [4,1] [=================>---------------------------] 39% est: 4s
## plot: [4,2] [=================>---------------------------] 41% est: 4s
## plot: [4,3] [==================>--------------------------] 42% est: 4s
## plot: [4,4] [===================>-------------------------] 44% est: 4s
## plot: [4,5] [===================>-------------------------] 45% est: 3s
## plot: [4,6] [====================>------------------------] 47% est: 3s
## plot: [4,7] [=====================>-----------------------] 48% est: 3s
## plot: [4,8] [=====================>-----------------------] 50% est: 3s
## plot: [5,1] [======================>----------------------] 52% est: 3s
## plot: [5,2] [=======================>---------------------] 53% est: 3s
## plot: [5,3] [========================>--------------------] 55% est: 3s
## plot: [5,4] [========================>--------------------] 56% est: 3s
## plot: [5,5] [=========================>-------------------] 58% est: 3s
## plot: [5,6] [==========================>------------------] 59% est: 2s
## plot: [5,7] [==========================>------------------] 61% est: 2s
## plot: [5,8] [===========================>-----------------] 62% est: 2s
## plot: [6,1] [============================>----------------] 64% est: 2s
## plot: [6,2] [=============================>---------------] 66% est: 2s
## plot: [6,3] [=============================>---------------] 67% est: 2s
## plot: [6,4] [==============================>--------------] 69% est: 2s
## plot: [6,5] [===============================>-------------] 70% est: 2s
## plot: [6,6] [===============================>-------------] 72% est: 2s
## plot: [6,7] [================================>------------] 73% est: 2s
## plot: [6,8] [=================================>-----------] 75% est: 2s
## plot: [7,1] [=================================>-----------] 77% est: 1s
## plot: [7,2] [==================================>----------] 78% est: 1s
## plot: [7,3] [===================================>---------] 80% est: 1s
## plot: [7,4] [====================================>--------] 81% est: 1s
## plot: [7,5] [====================================>--------] 83% est: 1s
## plot: [7,6] [=====================================>-------] 84% est: 1s
## plot: [7,7] [======================================>------] 86% est: 1s
## plot: [7,8] [======================================>------] 88% est: 1s
## plot: [8,1] [=======================================>-----] 89% est: 1s
## plot: [8,2] [========================================>----] 91% est: 1s
## plot: [8,3] [========================================>----] 92% est: 0s
## plot: [8,4] [=========================================>---] 94% est: 0s
## plot: [8,5] [==========================================>--] 95% est: 0s
## plot: [8,6] [===========================================>-] 97% est: 0s
## plot: [8,7] [===========================================>-] 98% est: 0s
## plot: [8,8] [=============================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.01
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.005
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.01
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [3,4] [=================================>-----------] 75% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 2.5e-005
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## [1] 10
## plot: [1,1] [---------------------------------------------] 1% est: 0s
## plot: [1,2] [>--------------------------------------------] 2% est: 7s
## plot: [1,3] [>--------------------------------------------] 3% est: 8s
## plot: [1,4] [=>-------------------------------------------] 4% est: 8s
## plot: [1,5] [=>-------------------------------------------] 5% est: 8s
## plot: [1,6] [==>------------------------------------------] 6% est: 8s
## plot: [1,7] [==>------------------------------------------] 7% est: 8s
## plot: [1,8] [===>-----------------------------------------] 8% est: 8s
## plot: [1,9] [===>-----------------------------------------] 9% est: 8s
## plot: [1,10] [===>----------------------------------------] 10% est: 8s
## plot: [2,1] [====>----------------------------------------] 11% est: 8s
## plot: [2,2] [====>----------------------------------------] 12% est: 8s
## plot: [2,3] [=====>---------------------------------------] 13% est: 8s
## plot: [2,4] [=====>---------------------------------------] 14% est: 8s
## plot: [2,5] [======>--------------------------------------] 15% est: 8s
## plot: [2,6] [======>--------------------------------------] 16% est: 7s
## plot: [2,7] [=======>-------------------------------------] 17% est: 7s
## plot: [2,8] [=======>-------------------------------------] 18% est: 7s
## plot: [2,9] [========>------------------------------------] 19% est: 7s
## plot: [2,10] [========>-----------------------------------] 20% est: 7s
## plot: [3,1] [========>------------------------------------] 21% est: 7s
## plot: [3,2] [=========>-----------------------------------] 22% est: 7s
## plot: [3,3] [=========>-----------------------------------] 23% est: 7s
## plot: [3,4] [==========>----------------------------------] 24% est: 7s
## plot: [3,5] [==========>----------------------------------] 25% est: 7s
## plot: [3,6] [===========>---------------------------------] 26% est: 7s
## plot: [3,7] [===========>---------------------------------] 27% est: 6s
## plot: [3,8] [============>--------------------------------] 28% est: 6s
## plot: [3,9] [============>--------------------------------] 29% est: 6s
## plot: [3,10] [============>-------------------------------] 30% est: 6s
## plot: [4,1] [=============>-------------------------------] 31% est: 6s
## plot: [4,2] [=============>-------------------------------] 32% est: 6s
## plot: [4,3] [==============>------------------------------] 33% est: 6s
## plot: [4,4] [==============>------------------------------] 34% est: 6s
## plot: [4,5] [===============>-----------------------------] 35% est: 6s
## plot: [4,6] [===============>-----------------------------] 36% est: 6s
## plot: [4,7] [================>----------------------------] 37% est: 6s
## plot: [4,8] [================>----------------------------] 38% est: 6s
## plot: [4,9] [=================>---------------------------] 39% est: 5s
## plot: [4,10] [=================>--------------------------] 40% est: 5s
## plot: [5,1] [=================>---------------------------] 41% est: 5s
## plot: [5,2] [==================>--------------------------] 42% est: 5s
## plot: [5,3] [==================>--------------------------] 43% est: 5s
## plot: [5,4] [===================>-------------------------] 44% est: 5s
## plot: [5,5] [===================>-------------------------] 45% est: 5s
## plot: [5,6] [====================>------------------------] 46% est: 5s
## plot: [5,7] [====================>------------------------] 47% est: 5s
## plot: [5,8] [=====================>-----------------------] 48% est: 5s
## plot: [5,9] [=====================>-----------------------] 49% est: 5s
## plot: [5,10] [=====================>----------------------] 50% est: 5s
## plot: [6,1] [======================>----------------------] 51% est: 4s
## plot: [6,2] [======================>----------------------] 52% est: 4s
## plot: [6,3] [=======================>---------------------] 53% est: 4s
## plot: [6,4] [=======================>---------------------] 54% est: 4s
## plot: [6,5] [========================>--------------------] 55% est: 4s
## plot: [6,6] [========================>--------------------] 56% est: 4s
## plot: [6,7] [=========================>-------------------] 57% est: 4s
## plot: [6,8] [=========================>-------------------] 58% est: 4s
## plot: [6,9] [==========================>------------------] 59% est: 4s
## plot: [6,10] [=========================>------------------] 60% est: 4s
## plot: [7,1] [==========================>------------------] 61% est: 4s
## plot: [7,2] [===========================>-----------------] 62% est: 3s
## plot: [7,3] [===========================>-----------------] 63% est: 3s
## plot: [7,4] [============================>----------------] 64% est: 3s
## plot: [7,5] [============================>----------------] 65% est: 3s
## plot: [7,6] [=============================>---------------] 66% est: 3s
## plot: [7,7] [=============================>---------------] 67% est: 3s
## plot: [7,8] [==============================>--------------] 68% est: 3s
## plot: [7,9] [==============================>--------------] 69% est: 3s
## plot: [7,10] [==============================>-------------] 70% est: 3s
## plot: [8,1] [===============================>-------------] 71% est: 3s
## plot: [8,2] [===============================>-------------] 72% est: 3s
## plot: [8,3] [================================>------------] 73% est: 2s
## plot: [8,4] [================================>------------] 74% est: 2s
## plot: [8,5] [=================================>-----------] 75% est: 2s
## plot: [8,6] [=================================>-----------] 76% est: 2s
## plot: [8,7] [==================================>----------] 77% est: 2s
## plot: [8,8] [==================================>----------] 78% est: 2s
## plot: [8,9] [===================================>---------] 79% est: 2s
## plot: [8,10] [==================================>---------] 80% est: 2s
## plot: [9,1] [===================================>---------] 81% est: 2s
## plot: [9,2] [====================================>--------] 82% est: 2s
## plot: [9,3] [====================================>--------] 83% est: 2s
## plot: [9,4] [=====================================>-------] 84% est: 1s
## plot: [9,5] [=====================================>-------] 85% est: 1s
## plot: [9,6] [======================================>------] 86% est: 1s
## plot: [9,7] [======================================>------] 87% est: 1s
## plot: [9,8] [=======================================>-----] 88% est: 1s
## plot: [9,9] [=======================================>-----] 89% est: 1s
## plot: [9,10] [=======================================>----] 90% est: 1s
## plot: [10,1] [=======================================>----] 91% est: 1s
## plot: [10,2] [=======================================>----] 92% est: 1s
## plot: [10,3] [========================================>---] 93% est: 1s
## plot: [10,4] [========================================>---] 94% est: 1s
## plot: [10,5] [=========================================>--] 95% est: 0s
## plot: [10,6] [=========================================>--] 96% est: 0s
## plot: [10,7] [==========================================>-] 97% est: 0s
## plot: [10,8] [==========================================>-] 98% est: 0s
## plot: [10,9] [===========================================>] 99% est: 0s
## plot: [10,10] [===========================================]100% est: 0s
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [2,2] [================>----------------------------] 38% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## plot: [4,2] [======================================>------] 88% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 8.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 5.03
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 25
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 8.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 5.03
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 25
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 1.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.1281e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 1.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.1281e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 8.5814e-030
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.0902
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 8.5814e-030
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.0902
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 3.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 6.9872e-016
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 3.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 6.9872e-016
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## plot: [1,3] [=======>-------------------------------------] 19% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [1,4] [==========>----------------------------------] 25% est: 2s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [1,1] [==>------------------------------------------] 6% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [1,2] [=====>---------------------------------------] 12% est: 1s
## plot: [1,3] [=======>-------------------------------------] 19% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [1,4] [==========>----------------------------------] 25% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [2,1] [=============>-------------------------------] 31% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [2,2] [================>----------------------------] 38% est: 1s
## plot: [2,3] [===================>-------------------------] 44% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [2,4] [=====================>-----------------------] 50% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [3,1] [========================>--------------------] 56% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [3,2] [===========================>-----------------] 62% est: 1s
## plot: [3,3] [==============================>--------------] 69% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [3,4] [=================================>-----------] 75% est: 1s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## plot: [4,1] [====================================>--------] 81% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## plot: [4,2] [======================================>------] 88% est: 0s
## plot: [4,3] [=========================================>---] 94% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## plot: [4,4] [=============================================]100% est: 0s
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 7.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.035
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0678e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 7.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.035
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0678e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1.7739e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.0404
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 1.7739e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 1.0404
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 3.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.577e-015
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 9.1204
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at -0.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 3.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.577e-015
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 9.1204
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 4.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.02
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 4.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.02
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0
## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 0.049062
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at -0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.2215
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1982.2
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger
## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)
###Temporal Independence of Variables
For each variable, the first graph (top left) shows the observed value of the data according to their sampling year. The second graph (top right) illustrates the observed trends in changes in data values over time. The third graph (bottom left) shows future forecasts of changes in values over time. On this graph, the blue line corresponds to the expected average trend of changes over time, the dark gray zone corresponds to a confidence interval of 80% and the pale gray zone corresponds to a 95% confidence interval. The fourth graph (bottom right) illustrates time series autocorrelation (ACF). An autocorrelation value greater than the 95% confidence interval illustrated by the dotted line indicates a possible dependency between the variable and the time of year (time). For example, a certain value of a variable observed in a given year could be explained by a certain event from a previous year (lag in time in years). It should be noted that the autocorrelation at offset time 0 is, by definition, equal to 1.
Below are the results of the Ljung-Box statistics test applied to each variable which confirming the results illustrated by the above graphs. A value of P (p-value) less than 0.05 makes it possible to assume that the residual values of a variable depend on the period of the year (time).
## [1] "Altitude"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.022571, df = 1, p-value = 0.8806
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15759, df = 2, p-value = 0.9242
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.43492, df = 3, p-value = 0.9329
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.95253, df = 4, p-value = 0.9169
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.274, df = 5, p-value = 0.9376
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9644, df = 6, p-value = 0.9229
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.018, df = 7, p-value = 0.6578
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5679, df = 8, p-value = 0.5839
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.459, df = 9, p-value = 0.1069
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.467, df = 10, p-value = 0.1528
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.476, df = 11, p-value = 0.1617
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.331, df = 12, p-value = 0.1765
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.412, df = 13, p-value = 0.1109
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.466, df = 14, p-value = 0.1479
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.786, df = 15, p-value = 0.1438
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 29.307, df = 16, p-value = 0.02194
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 34.2, df = 17, p-value = 0.00791
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 35.553, df = 18, p-value = 0.008047
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 36.949, df = 19, p-value = 0.008053
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 37.107, df = 20, p-value = 0.01136
##
##
## [1] "DistanceFromSource"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Depth.Avg"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2643e-05, df = 1, p-value = 0.9972
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0008783, df = 2, p-value = 0.9996
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0058457, df = 3, p-value = 0.9999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.8937, df = 4, p-value = 0.7553
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9668, df = 5, p-value = 0.8537
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1685, df = 6, p-value = 0.9036
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.4313, df = 7, p-value = 0.6075
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.6805, df = 8, p-value = 0.683
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.7111, df = 9, p-value = 0.7684
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.9534, df = 10, p-value = 0.8192
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.7088, df = 11, p-value = 0.8221
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.0129, df = 12, p-value = 0.8568
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.0223, df = 13, p-value = 0.901
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.0378, df = 14, p-value = 0.9332
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.2618, df = 15, p-value = 0.95
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.464, df = 16, p-value = 0.9632
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.5569, df = 17, p-value = 0.9751
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.794, df = 18, p-value = 0.3445
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.159, df = 19, p-value = 0.2764
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.635, df = 20, p-value = 0.3071
##
##
## [1] "Depth.BankfullMinusWetted"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0041446, df = 1, p-value = 0.9487
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.20216, df = 2, p-value = 0.9039
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.36548, df = 3, p-value = 0.9473
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.49071, df = 4, p-value = 0.9744
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0736, df = 5, p-value = 0.5389
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.093, df = 6, p-value = 0.6641
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.5163, df = 7, p-value = 0.7188
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.5164, df = 8, p-value = 0.8078
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.517, df = 9, p-value = 0.8742
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.524, df = 10, p-value = 0.9206
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.7389, df = 11, p-value = 0.9431
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.0017, df = 12, p-value = 0.9579
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.0817, df = 13, p-value = 0.9733
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.119, df = 14, p-value = 0.9841
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2514, df = 15, p-value = 0.9898
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2711, df = 16, p-value = 0.9942
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.4316, df = 17, p-value = 0.9963
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.454, df = 18, p-value = 0.998
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.4621, df = 19, p-value = 0.9989
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.5057, df = 20, p-value = 0.9994
##
##
## [1] "Depth.Max"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2334, df = 1, p-value = 0.2667
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3164, df = 2, p-value = 0.5178
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5382, df = 3, p-value = 0.6735
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5333, df = 4, p-value = 0.4728
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5848, df = 5, p-value = 0.6106
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.6816, df = 6, p-value = 0.7197
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.2414, df = 7, p-value = 0.4042
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.3048, df = 8, p-value = 0.5041
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.4341, df = 9, p-value = 0.592
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.5463, df = 10, p-value = 0.5756
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.388, df = 11, p-value = 0.4959
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.389, df = 12, p-value = 0.5819
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.514, df = 13, p-value = 0.6515
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.523, df = 14, p-value = 0.723
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.588, df = 15, p-value = 0.7812
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.909, df = 16, p-value = 0.7502
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.713, df = 17, p-value = 0.7552
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19, df = 18, p-value = 0.3918
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 23.599, df = 19, p-value = 0.212
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 23.645, df = 20, p-value = 0.2582
##
##
## [1] "Discharge"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.06865, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.078123, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.087809, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09771, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.10783, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.11818, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.12876, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.13957, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15063, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.16193, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.17348, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.18528, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.19735, df = 20, p-value = 1
##
##
## [1] "Macrophyte"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reach.CanopyCoverage"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016033, df = 3, p-value = 0.9995
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.01604, df = 4, p-value = 1
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016052, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016068, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016091, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016121, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016159, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016206, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016264, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016333, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016415, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016511, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016622, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.01675, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016895, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.017059, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.017243, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.01745, df = 20, p-value = 1
##
##
## [1] "Reach.Logging"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.06865, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.078123, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.087809, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09771, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.10783, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.11818, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.12876, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.13957, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15063, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.16193, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.17348, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.18528, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.19735, df = 20, p-value = 1
##
##
## [1] "Slope"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.4842, df = 1, p-value = 0.4865
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.6926, df = 2, p-value = 0.09572
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.375, df = 3, p-value = 0.01563
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.42, df = 4, p-value = 0.03392
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.603, df = 5, p-value = 0.0122
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.792, df = 6, p-value = 0.006772
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.092, df = 7, p-value = 0.01156
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.886, df = 8, p-value = 0.01078
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.327, df = 9, p-value = 0.016
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.535, df = 10, p-value = 0.02458
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.545, df = 11, p-value = 0.02814
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.591, df = 12, p-value = 0.04237
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.825, df = 13, p-value = 0.05814
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.182, df = 14, p-value = 0.07496
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.199, df = 15, p-value = 0.1027
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.371, df = 16, p-value = 0.1316
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.521, df = 17, p-value = 0.1655
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.605, df = 18, p-value = 0.2062
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.811, df = 19, p-value = 0.2458
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.874, df = 20, p-value = 0.295
##
##
## [1] "Velocity.Avg"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.16122, df = 1, p-value = 0.688
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3987, df = 2, p-value = 0.4969
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4529, df = 3, p-value = 0.6932
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.7704, df = 4, p-value = 0.7779
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9303, df = 5, p-value = 0.8587
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.016, df = 6, p-value = 0.9182
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1377, df = 7, p-value = 0.9518
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.8044, df = 8, p-value = 0.8743
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.826, df = 9, p-value = 0.9225
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.5978, df = 10, p-value = 0.9164
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.9069, df = 11, p-value = 0.9356
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.3473, df = 12, p-value = 0.8976
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5992, df = 13, p-value = 0.9216
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.6315, df = 14, p-value = 0.948
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.6624, df = 15, p-value = 0.9663
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.704, df = 16, p-value = 0.8274
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.705, df = 17, p-value = 0.8715
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.733, df = 18, p-value = 0.9053
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.733, df = 19, p-value = 0.9325
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.756, df = 20, p-value = 0.8426
##
##
## [1] "Velocity.Max"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5178, df = 1, p-value = 0.2179
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9898, df = 2, p-value = 0.3698
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.854, df = 3, p-value = 0.001946
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.858, df = 4, p-value = 0.005004
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.127, df = 5, p-value = 0.00182
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.655, df = 6, p-value = 0.002116
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.983, df = 7, p-value = 0.003795
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.468, df = 8, p-value = 0.000873
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 27.106, df = 9, p-value = 0.001343
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 28.153, df = 10, p-value = 0.001706
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 28.349, df = 11, p-value = 0.002862
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 28.391, df = 12, p-value = 0.004847
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 29.636, df = 13, p-value = 0.005313
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 29.662, df = 14, p-value = 0.008493
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 30.665, df = 15, p-value = 0.009738
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 37.379, df = 16, p-value = 0.001854
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 37.4, df = 17, p-value = 0.002969
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 38.11, df = 18, p-value = 0.003746
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 39.087, df = 19, p-value = 0.004304
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 41.764, df = 20, p-value = 0.002968
##
##
## [1] "Width.Bankfull"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0036875, df = 1, p-value = 0.9516
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0093136, df = 2, p-value = 0.9954
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.039745, df = 3, p-value = 0.9979
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.039765, df = 4, p-value = 0.9998
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.51831, df = 5, p-value = 0.9914
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0924, df = 6, p-value = 0.9819
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.857, df = 7, p-value = 0.8979
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7066, df = 8, p-value = 0.8826
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7125, df = 9, p-value = 0.9293
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7701, df = 10, p-value = 0.9571
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.5192, df = 11, p-value = 0.9034
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.6103, df = 12, p-value = 0.8148
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.1017, df = 13, p-value = 0.7652
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.13, df = 14, p-value = 0.7526
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.202, df = 15, p-value = 0.8068
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.539, df = 16, p-value = 0.775
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.362, df = 17, p-value = 0.6414
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.581, df = 18, p-value = 0.5521
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.574, df = 19, p-value = 0.4844
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.639, df = 20, p-value = 0.5454
##
##
## [1] "Width.Wetted"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0013964, df = 1, p-value = 0.9702
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.02773, df = 2, p-value = 0.9862
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.24865, df = 3, p-value = 0.9694
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.36351, df = 4, p-value = 0.9854
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.3968, df = 5, p-value = 0.9954
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.5841, df = 6, p-value = 0.9967
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3747, df = 7, p-value = 0.9863
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5495, df = 8, p-value = 0.9594
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5497, df = 9, p-value = 0.9795
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.7307, df = 10, p-value = 0.9871
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.3586, df = 11, p-value = 0.9851
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.11, df = 12, p-value = 0.9814
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.9312, df = 13, p-value = 0.9767
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.9596, df = 14, p-value = 0.9675
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.0692, df = 15, p-value = 0.9786
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.7598, df = 16, p-value = 0.9776
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.6655, df = 17, p-value = 0.9502
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.314, df = 18, p-value = 0.9212
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.833, df = 19, p-value = 0.8926
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.878, df = 20, p-value = 0.9202
##
##
## [1] "XSEC.VelEquationSlope"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09065, df = 1, p-value = 0.7634
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.46683, df = 2, p-value = 0.7918
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.73468, df = 3, p-value = 0.865
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0651, df = 4, p-value = 0.8998
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.39, df = 5, p-value = 0.9254
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9203, df = 6, p-value = 0.9269
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0888, df = 7, p-value = 0.9548
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.182, df = 8, p-value = 0.9749
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1838, df = 9, p-value = 0.9882
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.4858, df = 10, p-value = 0.9911
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8238, df = 11, p-value = 0.9394
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8485, df = 12, p-value = 0.9628
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.9141, df = 13, p-value = 0.9065
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.747, df = 14, p-value = 0.5466
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.883, df = 15, p-value = 0.6113
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.384, df = 16, p-value = 0.6445
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.925, df = 17, p-value = 0.6009
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.049, df = 18, p-value = 0.6586
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.07, df = 19, p-value = 0.7182
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.056, df = 20, p-value = 0.5182
##
##
## [1] "XSEC.VeloEquationIntercept"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09067, df = 1, p-value = 0.7633
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.4669, df = 2, p-value = 0.7918
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.73477, df = 3, p-value = 0.865
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0651, df = 4, p-value = 0.8998
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.39, df = 5, p-value = 0.9254
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9205, df = 6, p-value = 0.9269
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0891, df = 7, p-value = 0.9547
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1822, df = 8, p-value = 0.9749
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.184, df = 9, p-value = 0.9882
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.4861, df = 10, p-value = 0.9911
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.824, df = 11, p-value = 0.9394
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8487, df = 12, p-value = 0.9628
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.9141, df = 13, p-value = 0.9065
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.747, df = 14, p-value = 0.5466
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.883, df = 15, p-value = 0.6114
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.384, df = 16, p-value = 0.6445
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.925, df = 17, p-value = 0.6009
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.049, df = 18, p-value = 0.6586
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.07, df = 19, p-value = 0.7182
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.056, df = 20, p-value = 0.5182
##
##
## [1] "Rainfall01_JAN"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Rainfall06_JUN"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Snowfall06_JUN"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "SnowfallTotal_ANNUAL"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Temp01_JANMax"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Lake"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Drainage.Area"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "StreamDensity"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reg.Alpine"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reg.Forest"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reg.Lake"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reg.UnregenForest"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reg.Wetland"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Al"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "As"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "B"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Mg"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Ni"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Bedrock"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Boulder"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0001196, df = 1, p-value = 0.9913
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.062786, df = 2, p-value = 0.9691
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.51261, df = 3, p-value = 0.9161
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4325, df = 4, p-value = 0.3506
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.9088, df = 5, p-value = 0.4271
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.5222, df = 6, p-value = 0.4788
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.0315, df = 7, p-value = 0.3298
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.273, df = 8, p-value = 0.2464
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.292, df = 9, p-value = 0.3273
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.358, df = 10, p-value = 0.4097
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.613, df = 11, p-value = 0.4763
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.561, df = 12, p-value = 0.4816
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.629, df = 13, p-value = 0.5583
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.725, df = 14, p-value = 0.6284
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.117, df = 15, p-value = 0.6701
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.485, df = 16, p-value = 0.4895
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.401, df = 17, p-value = 0.06745
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.48, df = 18, p-value = 0.08928
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 27.776, df = 19, p-value = 0.08784
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 27.979, df = 20, p-value = 0.1099
##
##
## [1] "Cobble"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.093401, df = 1, p-value = 0.7599
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.25724, df = 2, p-value = 0.8793
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.30899, df = 3, p-value = 0.9583
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7584, df = 4, p-value = 0.4397
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7585, df = 5, p-value = 0.5847
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7851, df = 6, p-value = 0.7057
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.5606, df = 7, p-value = 0.5919
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.0143, df = 8, p-value = 0.5351
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.0153, df = 9, p-value = 0.6355
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.4541, df = 10, p-value = 0.682
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.7937, df = 11, p-value = 0.7317
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9013, df = 12, p-value = 0.7928
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.7217, df = 13, p-value = 0.7936
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.0726, df = 14, p-value = 0.8264
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.2095, df = 15, p-value = 0.8663
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.902, df = 16, p-value = 0.392
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.204, df = 17, p-value = 0.01419
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.281, df = 18, p-value = 0.02036
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.291, df = 19, p-value = 0.02898
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 33.834, df = 20, p-value = 0.02727
##
##
## [1] "Gravel"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0052624, df = 1, p-value = 0.9422
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.10324, df = 2, p-value = 0.9497
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.53223, df = 3, p-value = 0.9118
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0513, df = 4, p-value = 0.9019
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.8139, df = 5, p-value = 0.7287
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.9883, df = 6, p-value = 0.8103
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.3629, df = 7, p-value = 0.8495
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.3847, df = 8, p-value = 0.9079
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.4459, df = 9, p-value = 0.944
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5055, df = 10, p-value = 0.9669
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5736, df = 11, p-value = 0.9808
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4184, df = 12, p-value = 0.9746
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.9305, df = 13, p-value = 0.9486
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.9495, df = 14, p-value = 0.9677
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.7731, df = 15, p-value = 0.9326
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.73, df = 16, p-value = 0.7624
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.723, df = 17, p-value = 0.6866
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.866, df = 18, p-value = 0.7378
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.201, df = 19, p-value = 0.7718
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.077, df = 20, p-value = 0.7118
##
##
## [1] "Pebble"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.019631, df = 1, p-value = 0.8886
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.031409, df = 2, p-value = 0.9844
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.035876, df = 3, p-value = 0.9982
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.37146, df = 4, p-value = 0.9847
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.42267, df = 5, p-value = 0.9947
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.65254, df = 6, p-value = 0.9955
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.96764, df = 7, p-value = 0.9953
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.953, df = 8, p-value = 0.9824
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0237, df = 9, p-value = 0.9911
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1919, df = 10, p-value = 0.9946
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.615, df = 11, p-value = 0.9949
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.7598, df = 12, p-value = 0.997
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.788, df = 13, p-value = 0.9986
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.196, df = 14, p-value = 0.9987
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.2034, df = 15, p-value = 0.9994
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.5181, df = 16, p-value = 0.9619
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.274, df = 17, p-value = 0.7177
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.511, df = 18, p-value = 0.7604
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.532, df = 19, p-value = 0.7519
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.108, df = 20, p-value = 0.7099
##
##
## [1] "Sand"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.013182, df = 1, p-value = 0.9086
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.065338, df = 2, p-value = 0.9679
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.21859, df = 3, p-value = 0.9745
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.68888, df = 4, p-value = 0.9527
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.93801, df = 5, p-value = 0.9674
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0147, df = 6, p-value = 0.9851
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.0913, df = 7, p-value = 0.8764
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.6141, df = 8, p-value = 0.6904
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.7252, df = 9, p-value = 0.7671
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.1855, df = 10, p-value = 0.7994
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.2538, df = 11, p-value = 0.8559
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.2071, df = 12, p-value = 0.8436
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.419, df = 13, p-value = 0.8793
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.6688, df = 14, p-value = 0.9059
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.0352, df = 15, p-value = 0.9224
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.0667, df = 16, p-value = 0.9469
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.3545, df = 17, p-value = 0.9584
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.0798, df = 18, p-value = 0.9579
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.6406, df = 19, p-value = 0.9613
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.9768, df = 20, p-value = 0.9686
##
##
## [1] "Silt.Clay"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.033121, df = 1, p-value = 0.8556
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.13112, df = 2, p-value = 0.9365
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.7537, df = 3, p-value = 0.8605
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.357, df = 4, p-value = 0.8516
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4328, df = 5, p-value = 0.9207
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.1438, df = 6, p-value = 0.4073
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5013, df = 7, p-value = 0.4826
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9072, df = 8, p-value = 0.4426
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9098, df = 9, p-value = 0.5433
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.1596, df = 10, p-value = 0.6132
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.365, df = 11, p-value = 0.4132
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.622, df = 12, p-value = 0.4765
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.64, df = 13, p-value = 0.5574
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.835, df = 14, p-value = 0.6195
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.835, df = 15, p-value = 0.6914
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.969, df = 16, p-value = 0.7461
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.504, df = 17, p-value = 0.6311
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.73, df = 18, p-value = 0.6114
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.151, df = 19, p-value = 0.5796
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.579, df = 20, p-value = 0.6151
##
##
## [1] "D50"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0094578, df = 1, p-value = 0.9225
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.066726, df = 2, p-value = 0.9672
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.10389, df = 3, p-value = 0.9914
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.2994, df = 4, p-value = 0.6809
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.3396, df = 5, p-value = 0.8004
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.1121, df = 6, p-value = 0.7946
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.9086, df = 7, p-value = 0.6711
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.379, df = 8, p-value = 0.4963
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.4178, df = 9, p-value = 0.5937
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9207, df = 10, p-value = 0.6366
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.1725, df = 11, p-value = 0.6978
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.1743, df = 12, p-value = 0.7714
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.285, df = 13, p-value = 0.587
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.668, df = 14, p-value = 0.6329
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.515, df = 15, p-value = 0.415
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.777, df = 16, p-value = 0.2804
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 24.66, df = 17, p-value = 0.1026
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 24.688, df = 18, p-value = 0.1337
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 24.705, df = 19, p-value = 0.1705
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 24.842, df = 20, p-value = 0.2076
##
##
## [1] "Dg"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.061242, df = 1, p-value = 0.8045
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.061564, df = 2, p-value = 0.9697
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2409, df = 3, p-value = 0.7432
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.0392, df = 4, p-value = 0.1962
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.3421, df = 5, p-value = 0.2743
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4529, df = 6, p-value = 0.3744
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.7754, df = 7, p-value = 0.2692
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.686, df = 8, p-value = 0.2201
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.708, df = 9, p-value = 0.2963
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.774, df = 10, p-value = 0.3754
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.857, df = 11, p-value = 0.4553
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.562, df = 12, p-value = 0.4815
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.504, df = 13, p-value = 0.4868
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.161, df = 14, p-value = 0.5139
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.487, df = 15, p-value = 0.5648
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.891, df = 16, p-value = 0.2744
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.182, df = 17, p-value = 0.01429
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.403, df = 18, p-value = 0.01969
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.667, df = 19, p-value = 0.02626
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 34.708, df = 20, p-value = 0.02172
##
##
## [1] "SlopeAvg"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.06865, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.078123, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.087809, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09771, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.10783, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.11818, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.12876, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.13957, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15063, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.16193, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.17348, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.18528, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.19735, df = 20, p-value = 1
##
##
## [1] "Ag"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Ba"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "CO3"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "General.Alkalinity"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0040192, df = 1, p-value = 0.9495
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.010414, df = 2, p-value = 0.9948
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.026789, df = 3, p-value = 0.9988
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.26789, df = 4, p-value = 0.9918
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.44208, df = 5, p-value = 0.9941
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.98082, df = 6, p-value = 0.9863
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.1453, df = 7, p-value = 0.9921
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.6167, df = 8, p-value = 0.9906
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.4446, df = 9, p-value = 0.49
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.4979, df = 10, p-value = 0.4856
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.7542, df = 11, p-value = 0.5526
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.7714, df = 12, p-value = 0.636
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.429, df = 13, p-value = 0.6585
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.624, df = 14, p-value = 0.7153
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.722, df = 15, p-value = 0.772
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.518, df = 16, p-value = 0.7764
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.618, df = 17, p-value = 0.8227
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.401, df = 18, p-value = 0.8259
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.003, df = 19, p-value = 0.7835
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.3, df = 20, p-value = 0.759
##
##
## [1] "General.CarbonDOC"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "General.Conductivity"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.025382, df = 1, p-value = 0.8734
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3333, df = 2, p-value = 0.5134
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.9122, df = 3, p-value = 0.2711
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8473, df = 4, p-value = 0.3033
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.9053, df = 5, p-value = 0.4275
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.8637, df = 6, p-value = 0.4386
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.1256, df = 7, p-value = 0.3217
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.2379, df = 8, p-value = 0.4106
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.3496, df = 9, p-value = 0.4993
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.647, df = 10, p-value = 0.3857
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.65, df = 11, p-value = 0.4731
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.652, df = 12, p-value = 0.559
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.619, df = 13, p-value = 0.4776
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.73, df = 14, p-value = 0.5479
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.843, df = 15, p-value = 0.6144
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.69, df = 16, p-value = 0.4748
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.868, df = 17, p-value = 0.3972
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.895, df = 18, p-value = 0.4626
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.705, df = 19, p-value = 0.4759
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.3, df = 20, p-value = 0.1902
##
##
## [1] "General.DO"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3328e-06, df = 1, p-value = 0.9991
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0236, df = 2, p-value = 0.5994
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0342, df = 3, p-value = 0.793
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.0452, df = 4, p-value = 0.9029
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0181, df = 5, p-value = 0.8466
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0323, df = 6, p-value = 0.9167
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1449, df = 7, p-value = 0.9514
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.6422, df = 8, p-value = 0.9548
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.7435, df = 9, p-value = 0.9736
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.8901, df = 10, p-value = 0.9839
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.2531, df = 11, p-value = 0.9869
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.4937, df = 12, p-value = 0.9909
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.6425, df = 13, p-value = 0.9944
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.8646, df = 14, p-value = 0.9962
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.2518, df = 15, p-value = 0.9968
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.463, df = 16, p-value = 0.2001
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.654, df = 17, p-value = 0.2422
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.043, df = 18, p-value = 0.2772
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.637, df = 19, p-value = 0.3027
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.717, df = 20, p-value = 0.3561
##
##
## [1] "General.pH"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.41292, df = 1, p-value = 0.5205
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.44517, df = 2, p-value = 0.8004
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.44551, df = 3, p-value = 0.9307
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.83462, df = 4, p-value = 0.9337
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.86684, df = 5, p-value = 0.9726
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.8676, df = 6, p-value = 0.9901
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2332, df = 7, p-value = 0.9901
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2733, df = 8, p-value = 0.9959
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2801, df = 9, p-value = 0.9985
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5017, df = 10, p-value = 0.9989
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5372, df = 11, p-value = 0.9996
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5395, df = 12, p-value = 0.9998
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.7705, df = 13, p-value = 0.9999
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.7993, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.7996, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.026, df = 16, p-value = 0.4512
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.256, df = 17, p-value = 0.5057
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.256, df = 18, p-value = 0.5747
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.257, df = 19, p-value = 0.6401
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.492, df = 20, p-value = 0.6857
##
##
## [1] "General.SolidsTDS"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "General.SolidsTSS"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.45047, df = 1, p-value = 0.5021
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.79126, df = 2, p-value = 0.6733
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.80385, df = 3, p-value = 0.8485
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.85918, df = 4, p-value = 0.9303
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.88019, df = 5, p-value = 0.9716
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.95043, df = 6, p-value = 0.9874
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.214, df = 7, p-value = 0.9906
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2306, df = 8, p-value = 0.9963
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5408, df = 9, p-value = 0.9968
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9054, df = 10, p-value = 0.997
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0639, df = 11, p-value = 0.9983
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0641, df = 12, p-value = 0.9993
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.066, df = 13, p-value = 0.9997
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.0304, df = 14, p-value = 0.999
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.2068, df = 15, p-value = 0.997
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.024, df = 16, p-value = 0.9956
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.5142, df = 17, p-value = 0.9543
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.4861, df = 18, p-value = 0.9474
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.159, df = 19, p-value = 0.9489
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.063, df = 20, p-value = 0.9446
##
##
## [1] "General.SpCond"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.00718, df = 1, p-value = 0.9325
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.18363, df = 2, p-value = 0.9123
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.1863, df = 3, p-value = 0.9798
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.30805, df = 4, p-value = 0.9893
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7147, df = 5, p-value = 0.5912
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0056, df = 6, p-value = 0.6759
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.6445, df = 7, p-value = 0.5818
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.6468, df = 8, p-value = 0.5752
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.2764, df = 9, p-value = 0.5065
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.011, df = 10, p-value = 0.3567
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.449, df = 11, p-value = 0.4065
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.494, df = 12, p-value = 0.4871
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.1, df = 13, p-value = 0.3012
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.663, df = 14, p-value = 0.2746
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.013, df = 15, p-value = 0.3181
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.18, df = 16, p-value = 0.3135
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.443, df = 17, p-value = 0.3037
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.571, df = 18, p-value = 0.3016
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.579, df = 19, p-value = 0.3605
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.71, df = 20, p-value = 0.3033
##
##
## [1] "General.TempAir"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0082471, df = 1, p-value = 0.9276
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.62841, df = 2, p-value = 0.7304
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5932, df = 3, p-value = 0.3089
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.1067, df = 4, p-value = 0.2765
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.2682, df = 5, p-value = 0.281
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.4952, df = 6, p-value = 0.2775
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.8657, df = 7, p-value = 0.2624
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.5584, df = 8, p-value = 0.2974
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.811, df = 9, p-value = 0.2889
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.693, df = 10, p-value = 0.3062
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.949, df = 11, p-value = 0.3675
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.464, df = 12, p-value = 0.4092
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.414, df = 13, p-value = 0.4164
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.415, df = 14, p-value = 0.4941
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.905, df = 15, p-value = 0.4583
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.409, df = 16, p-value = 0.1633
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.577, df = 17, p-value = 0.2015
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.6, df = 18, p-value = 0.2502
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.613, df = 19, p-value = 0.304
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.629, df = 20, p-value = 0.361
##
##
## [1] "General.TempWater"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0011481, df = 1, p-value = 0.973
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.168, df = 2, p-value = 0.5577
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.1733, df = 3, p-value = 0.7594
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.252, df = 4, p-value = 0.8695
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.3577, df = 5, p-value = 0.7978
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.3842, df = 6, p-value = 0.8812
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.4915, df = 7, p-value = 0.9277
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.8375, df = 8, p-value = 0.9441
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.9014, df = 9, p-value = 0.9681
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.9739, df = 10, p-value = 0.982
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.226, df = 11, p-value = 0.9874
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.3924, df = 12, p-value = 0.9921
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.4762, df = 13, p-value = 0.9956
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.6068, df = 14, p-value = 0.9974
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.9316, df = 15, p-value = 0.998
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.189, df = 16, p-value = 0.259
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.299, df = 17, p-value = 0.3117
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.961, df = 18, p-value = 0.335
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.036, df = 19, p-value = 0.3348
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.732, df = 20, p-value = 0.3552
##
##
## [1] "General.Turbidity"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.027458, df = 1, p-value = 0.8684
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.062214, df = 2, p-value = 0.9694
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.22918, df = 3, p-value = 0.9727
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9146, df = 4, p-value = 0.7515
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9149, df = 5, p-value = 0.8608
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.3891, df = 6, p-value = 0.8807
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.7862, df = 7, p-value = 0.904
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.0038, df = 8, p-value = 0.7572
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.0038, df = 9, p-value = 0.834
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.1764, df = 10, p-value = 0.8791
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4264, df = 11, p-value = 0.8435
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4776, df = 12, p-value = 0.8901
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5258, df = 13, p-value = 0.9249
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.6982, df = 14, p-value = 0.9457
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.157, df = 15, p-value = 0.7414
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.234, df = 16, p-value = 0.7948
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.464, df = 17, p-value = 0.2512
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 23.242, df = 18, p-value = 0.1815
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 27.988, df = 19, p-value = 0.08366
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 28.063, df = 20, p-value = 0.1079
##
##
## [1] "Nitrogen.NH3"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.06865, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.078123, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.087809, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09771, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.10783, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.11818, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.12876, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.13957, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15063, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.16193, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.17348, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.18528, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.19735, df = 20, p-value = 1
##
##
## [1] "Nitrogen.NO2"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15003, df = 1, p-value = 0.6985
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.58745, df = 2, p-value = 0.7455
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.59516, df = 3, p-value = 0.8975
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.9548, df = 4, p-value = 0.7441
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8218, df = 5, p-value = 0.438
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.849, df = 6, p-value = 0.5633
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.9777, df = 7, p-value = 0.2543
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.2958, df = 8, p-value = 0.318
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.3165, df = 9, p-value = 0.4086
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.9935, df = 10, p-value = 0.4411
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.9963, df = 11, p-value = 0.5307
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.251, df = 12, p-value = 0.4258
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.404, df = 13, p-value = 0.4949
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.593, df = 14, p-value = 0.5588
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.19, df = 15, p-value = 0.5876
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.194, df = 16, p-value = 0.6586
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.352, df = 17, p-value = 0.7123
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.758, df = 18, p-value = 0.7448
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.287, df = 19, p-value = 0.7667
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.909, df = 20, p-value = 0.7816
##
##
## [1] "Nitrogen.NO2.NO3"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.018278, df = 1, p-value = 0.8925
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.02309, df = 2, p-value = 0.9885
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.49792, df = 3, p-value = 0.9193
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2447, df = 4, p-value = 0.8707
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2451, df = 5, p-value = 0.9405
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.1951, df = 6, p-value = 0.784
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.3784, df = 7, p-value = 0.8479
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5878, df = 8, p-value = 0.8923
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.8076, df = 9, p-value = 0.9236
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.6263, df = 10, p-value = 0.9147
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.7291, df = 11, p-value = 0.9436
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.7342, df = 12, p-value = 0.9663
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.1709, df = 13, p-value = 0.9397
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.7393, df = 14, p-value = 0.8474
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.8086, df = 15, p-value = 0.8316
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.959, df = 16, p-value = 0.812
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.935, df = 17, p-value = 0.7405
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.955, df = 18, p-value = 0.7942
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.356, df = 19, p-value = 0.7626
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.376, df = 20, p-value = 0.8109
##
##
## [1] "Nitrogen.NO3"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0064548, df = 1, p-value = 0.936
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2978, df = 2, p-value = 0.5226
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3029, df = 3, p-value = 0.7285
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.704, df = 4, p-value = 0.79
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.0982, df = 5, p-value = 0.6848
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.1099, df = 6, p-value = 0.7949
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5044, df = 7, p-value = 0.8348
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5231, df = 8, p-value = 0.8974
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5298, df = 9, p-value = 0.9396
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.9053, df = 10, p-value = 0.9515
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.977, df = 11, p-value = 0.9706
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.2911, df = 12, p-value = 0.9776
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4341, df = 13, p-value = 0.9856
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.501, df = 14, p-value = 0.9916
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.7957, df = 15, p-value = 0.9937
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.1646, df = 16, p-value = 0.9949
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2716, df = 17, p-value = 0.9969
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.5532, df = 18, p-value = 0.9977
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.8903, df = 19, p-value = 0.9982
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.1068, df = 20, p-value = 0.9963
##
##
## [1] "Nitrogen.TDN"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.23293, df = 1, p-value = 0.6294
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.67078, df = 2, p-value = 0.7151
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.6662, df = 3, p-value = 0.6445
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1324, df = 4, p-value = 0.7114
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1436, df = 5, p-value = 0.8289
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4026, df = 6, p-value = 0.6224
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4117, df = 7, p-value = 0.7313
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4125, df = 8, p-value = 0.8181
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.4249, df = 9, p-value = 0.8813
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5827, df = 10, p-value = 0.7642
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5877, df = 11, p-value = 0.8314
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.6017, df = 12, p-value = 0.8828
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.3782, df = 13, p-value = 0.8816
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.315, df = 14, p-value = 0.7388
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.986, df = 15, p-value = 0.7536
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.933, df = 16, p-value = 0.6777
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.59, df = 17, p-value = 0.625
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.788, df = 18, p-value = 0.6765
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.091, df = 19, p-value = 0.7168
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.096, df = 20, p-value = 0.7709
##
##
## [1] "Nitrogen.TN"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.030108, df = 1, p-value = 0.8622
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.33693, df = 2, p-value = 0.845
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.61062, df = 3, p-value = 0.894
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.84472, df = 4, p-value = 0.9324
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.1941, df = 5, p-value = 0.9454
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4381, df = 6, p-value = 0.9635
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1392, df = 7, p-value = 0.9517
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5078, df = 8, p-value = 0.9614
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2457, df = 9, p-value = 0.8124
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3018, df = 10, p-value = 0.8701
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3022, df = 11, p-value = 0.9157
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3022, df = 12, p-value = 0.9471
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4908, df = 13, p-value = 0.9265
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4921, df = 14, p-value = 0.9525
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.898, df = 15, p-value = 0.9278
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.986, df = 16, p-value = 0.7449
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.217, df = 17, p-value = 0.7868
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.303, df = 18, p-value = 0.8312
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.309, df = 19, p-value = 0.872
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.333, df = 20, p-value = 0.9042
##
##
## [1] "Nitrogen.TN_Organic"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Phosphorus.OrthoP"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.030108, df = 1, p-value = 0.8622
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.33693, df = 2, p-value = 0.845
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.61062, df = 3, p-value = 0.894
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.84472, df = 4, p-value = 0.9324
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.1941, df = 5, p-value = 0.9454
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4381, df = 6, p-value = 0.9635
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1392, df = 7, p-value = 0.9517
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5078, df = 8, p-value = 0.9614
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2457, df = 9, p-value = 0.8124
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3018, df = 10, p-value = 0.8701
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3022, df = 11, p-value = 0.9157
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3022, df = 12, p-value = 0.9471
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4908, df = 13, p-value = 0.9265
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4921, df = 14, p-value = 0.9525
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.898, df = 15, p-value = 0.9278
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.986, df = 16, p-value = 0.7449
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.217, df = 17, p-value = 0.7868
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.303, df = 18, p-value = 0.8312
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.309, df = 19, p-value = 0.872
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.333, df = 20, p-value = 0.9042
##
##
## [1] "Phosphorus.TDP"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0026042, df = 1, p-value = 0.9593
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0036357, df = 2, p-value = 0.9982
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.08005, df = 3, p-value = 0.9941
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.53248, df = 4, p-value = 0.9703
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.53269, df = 5, p-value = 0.9909
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0413, df = 6, p-value = 0.9159
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0477, df = 7, p-value = 0.9572
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0759, df = 8, p-value = 0.9786
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0764, df = 9, p-value = 0.9902
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0751, df = 10, p-value = 0.9439
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0763, df = 11, p-value = 0.9676
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0841, df = 12, p-value = 0.9819
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.5939, df = 13, p-value = 0.9831
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.5048, df = 14, p-value = 0.9521
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.5435, df = 15, p-value = 0.9408
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.059, df = 16, p-value = 0.8635
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.515, df = 17, p-value = 0.8286
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.515, df = 18, p-value = 0.8712
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.522, df = 19, p-value = 0.905
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.609, df = 20, p-value = 0.9289
##
##
## [1] "Phosphorus.TP"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.030108, df = 1, p-value = 0.8622
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.33693, df = 2, p-value = 0.845
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.61062, df = 3, p-value = 0.894
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.84472, df = 4, p-value = 0.9324
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.1941, df = 5, p-value = 0.9454
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4381, df = 6, p-value = 0.9635
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1392, df = 7, p-value = 0.9517
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5078, df = 8, p-value = 0.9614
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2457, df = 9, p-value = 0.8124
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3018, df = 10, p-value = 0.8701
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3022, df = 11, p-value = 0.9157
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3022, df = 12, p-value = 0.9471
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4908, df = 13, p-value = 0.9265
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4921, df = 14, p-value = 0.9525
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.898, df = 15, p-value = 0.9278
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.986, df = 16, p-value = 0.7449
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.217, df = 17, p-value = 0.7868
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.303, df = 18, p-value = 0.8312
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.309, df = 19, p-value = 0.872
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.333, df = 20, p-value = 0.9042
## [1] "Reach.Pools"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016729, df = 1, p-value = 0.8971
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2227, df = 2, p-value = 0.5426
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5589, df = 3, p-value = 0.4647
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.3468, df = 4, p-value = 0.3611
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.1408, df = 5, p-value = 0.2928
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.7398, df = 6, p-value = 0.2578
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.7983, df = 7, p-value = 0.3507
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.8078, df = 8, p-value = 0.4525
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.139, df = 9, p-value = 0.1175
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.586, df = 10, p-value = 0.1479
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.712, df = 11, p-value = 0.1167
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.563, df = 12, p-value = 0.1296
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.423, df = 13, p-value = 0.08516
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.728, df = 14, p-value = 0.1088
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.086, df = 15, p-value = 0.1341
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 21.62, df = 16, p-value = 0.1559
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.141, df = 17, p-value = 0.1793
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.233, df = 18, p-value = 0.2218
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.451, df = 19, p-value = 0.2624
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.69, df = 20, p-value = 0.3043
##
##
## [1] "Reach.Rapids"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 1, p-value = NA
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 2, p-value = NA
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 3, p-value = NA
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 4, p-value = NA
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 5, p-value = NA
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 6, p-value = NA
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 7, p-value = NA
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 8, p-value = NA
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 9, p-value = NA
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 10, p-value = NA
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 11, p-value = NA
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 12, p-value = NA
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 13, p-value = NA
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 14, p-value = NA
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 15, p-value = NA
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 16, p-value = NA
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 17, p-value = NA
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 18, p-value = NA
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 19, p-value = NA
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = NaN, df = 20, p-value = NA
##
##
## [1] "Reach.Riffles"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0061691, df = 1, p-value = 0.9374
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0069238, df = 2, p-value = 0.9965
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.25912, df = 3, p-value = 0.9675
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3391, df = 4, p-value = 0.8547
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4607, df = 5, p-value = 0.9176
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5454, df = 6, p-value = 0.9564
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.8965, df = 7, p-value = 0.4397
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.3336, df = 8, p-value = 0.5011
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.6418, df = 9, p-value = 0.5706
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9829, df = 10, p-value = 0.6305
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.8615, df = 11, p-value = 0.5429
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.463, df = 12, p-value = 0.5754
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.797, df = 13, p-value = 0.6278
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.803, df = 14, p-value = 0.7015
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.803, df = 15, p-value = 0.7664
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.323, df = 16, p-value = 0.5747
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.744, df = 17, p-value = 0.238
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.893, df = 18, p-value = 0.1947
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.152, df = 19, p-value = 0.1556
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.187, df = 20, p-value = 0.1944
##
##
## [1] "Reach.StraightRun"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.06865, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.078123, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.087809, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09771, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.097779, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.097861, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.097957, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.098068, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.098196, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.098341, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.098505, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.09869, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.098896, df = 20, p-value = 1
##
##
## [1] "Veg.Coniferous"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059415, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059453, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0595, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059558, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059627, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059709, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059805, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059916, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060044, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060189, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060353, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060538, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060744, df = 20, p-value = 1
##
##
## [1] "Veg.Deciduous"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059415, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059453, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0595, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059558, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059627, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059709, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059805, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059916, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060044, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060189, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060353, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060538, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060744, df = 20, p-value = 1
##
##
## [1] "Veg.GrassesFerns"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0079245, df = 1, p-value = 0.9291
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.016029, df = 2, p-value = 0.992
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.024317, df = 3, p-value = 0.999
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.032793, df = 4, p-value = 0.9999
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.041461, df = 5, p-value = 1
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.050323, df = 6, p-value = 1
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059385, df = 7, p-value = 1
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059415, df = 8, p-value = 1
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059453, df = 9, p-value = 1
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0595, df = 10, p-value = 1
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059558, df = 11, p-value = 1
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059627, df = 12, p-value = 1
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059709, df = 13, p-value = 1
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059805, df = 14, p-value = 1
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.059916, df = 15, p-value = 1
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060044, df = 16, p-value = 1
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060189, df = 17, p-value = 1
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060353, df = 18, p-value = 1
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060538, df = 19, p-value = 1
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.060744, df = 20, p-value = 1
## [1] "StreamOrder"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0061684, df = 1, p-value = 0.9374
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0069211, df = 2, p-value = 0.9965
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.25911, df = 3, p-value = 0.9675
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.339, df = 4, p-value = 0.8547
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.4606, df = 5, p-value = 0.9176
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5453, df = 6, p-value = 0.9564
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.8966, df = 7, p-value = 0.4397
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.3337, df = 8, p-value = 0.5011
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.6419, df = 9, p-value = 0.5706
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9829, df = 10, p-value = 0.6305
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.8616, df = 11, p-value = 0.5429
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.463, df = 12, p-value = 0.5754
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.797, df = 13, p-value = 0.6278
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.803, df = 14, p-value = 0.7015
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.803, df = 15, p-value = 0.7664
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.323, df = 16, p-value = 0.5747
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 20.744, df = 17, p-value = 0.2379
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.894, df = 18, p-value = 0.1947
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.152, df = 19, p-value = 0.1556
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.187, df = 20, p-value = 0.1944
##
##
## [1] "Reach.DomStreamsideVeg"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.79473, df = 1, p-value = 0.3727
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.7366, df = 2, p-value = 0.1544
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.241, df = 3, p-value = 0.0646
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.8702, df = 4, p-value = 0.06443
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.9209, df = 5, p-value = 0.1123
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.6178, df = 6, p-value = 0.1417
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.083, df = 7, p-value = 0.1839
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.106, df = 8, p-value = 0.2577
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.319, df = 9, p-value = 0.3253
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.611, df = 10, p-value = 0.3886
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.664, df = 11, p-value = 0.4718
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.526, df = 12, p-value = 0.4844
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.135, df = 13, p-value = 0.5166
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.334, df = 14, p-value = 0.5004
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.729, df = 15, p-value = 0.5462
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.033, df = 16, p-value = 0.5962
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.302, df = 17, p-value = 0.5025
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 19.657, df = 18, p-value = 0.3524
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.799, df = 19, p-value = 0.1359
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 25.805, df = 20, p-value = 0.1723
##
##
## [1] "XSEC.VelInstrumentDirect"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.056089, df = 1, p-value = 0.8128
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.11257, df = 2, p-value = 0.9453
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.5743, df = 3, p-value = 0.3113
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.6189, df = 4, p-value = 0.46
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.9051, df = 5, p-value = 0.1615
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.154, df = 6, p-value = 0.02796
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.311, df = 7, p-value = 0.02242
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.494, df = 8, p-value = 0.01782
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.504, df = 9, p-value = 0.02976
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.53, df = 10, p-value = 0.04665
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.076, df = 11, p-value = 0.02379
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 22.209, df = 12, p-value = 0.03524
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.4, df = 13, p-value = 0.01502
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.713, df = 14, p-value = 0.02098
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.852, df = 15, p-value = 0.02996
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.882, df = 16, p-value = 0.04281
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 27.881, df = 17, p-value = 0.04634
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 28.568, df = 18, p-value = 0.05393
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 29.16, df = 19, p-value = 0.06352
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 30.752, df = 20, p-value = 0.05855
##
##
## [1] "XSEC.VelMethod"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.0002809, df = 1, p-value = 0.9866
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.1119, df = 2, p-value = 0.9456
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.2681, df = 3, p-value = 0.9659
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.6824, df = 4, p-value = 0.9535
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0403, df = 5, p-value = 0.8435
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0909, df = 6, p-value = 0.9112
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.1148, df = 7, p-value = 0.9532
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.1206, df = 8, p-value = 0.9266
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0433, df = 9, p-value = 0.9085
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0686, df = 10, p-value = 0.9442
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8183, df = 11, p-value = 0.9396
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3484, df = 12, p-value = 0.9453
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.4428, df = 13, p-value = 0.9285
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 11.87, df = 14, p-value = 0.6167
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 12.689, df = 15, p-value = 0.6263
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.594, df = 16, p-value = 0.6289
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.014, df = 17, p-value = 0.6661
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.455, df = 18, p-value = 0.699
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.458, df = 19, p-value = 0.7564
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.496, df = 20, p-value = 0.8045
##
##
## [1] "Dominant.1st"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.41851, df = 1, p-value = 0.5177
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.54031, df = 2, p-value = 0.7633
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.839, df = 3, p-value = 0.6065
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.0514, df = 4, p-value = 0.1332
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.062, df = 5, p-value = 0.2161
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.5805, df = 6, p-value = 0.2705
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.0497, df = 7, p-value = 0.2491
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.3425, df = 8, p-value = 0.3142
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 10.724, df = 9, p-value = 0.2951
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.779, df = 10, p-value = 0.1833
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 13.895, df = 11, p-value = 0.2389
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 14.663, df = 12, p-value = 0.2604
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.75, df = 13, p-value = 0.1672
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.755, df = 14, p-value = 0.2182
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.813, df = 15, p-value = 0.2726
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 26.843, df = 16, p-value = 0.04326
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 37.979, df = 17, p-value = 0.002474
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 37.995, df = 18, p-value = 0.00388
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 38.005, df = 19, p-value = 0.005926
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 40.139, df = 20, p-value = 0.004796
##
##
## [1] "Dominant.2nd"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.38317, df = 1, p-value = 0.5359
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.54557, df = 2, p-value = 0.7613
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.64815, df = 3, p-value = 0.8853
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.7292, df = 4, p-value = 0.7854
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.8295, df = 5, p-value = 0.8722
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.2597, df = 6, p-value = 0.8943
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.5485, df = 7, p-value = 0.9234
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.2147, df = 8, p-value = 0.8372
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.2584, df = 9, p-value = 0.8936
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.3189, df = 10, p-value = 0.9318
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.7997, df = 11, p-value = 0.9405
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.8022, df = 12, p-value = 0.9643
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2727, df = 13, p-value = 0.9687
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.2807, df = 14, p-value = 0.9815
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.3209, df = 15, p-value = 0.989
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 17.261, df = 16, p-value = 0.3689
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 36.703, df = 17, p-value = 0.003691
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 36.906, df = 18, p-value = 0.00539
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 36.946, df = 19, p-value = 0.008059
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 37.505, df = 20, p-value = 0.01017
##
##
## [1] "Embeddedness"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.2764, df = 1, p-value = 0.2586
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.5678, df = 2, p-value = 0.4566
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.5955, df = 3, p-value = 0.05516
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 15.896, df = 4, p-value = 0.003162
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 16.044, df = 5, p-value = 0.006719
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 18.685, df = 6, p-value = 0.00473
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 23.705, df = 7, p-value = 0.001284
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 24.591, df = 8, p-value = 0.001823
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 28.307, df = 9, p-value = 0.0008475
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.772, df = 10, p-value = 0.0002975
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 32.988, df = 11, p-value = 0.0005286
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 34.765, df = 12, p-value = 0.0005105
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 39.192, df = 13, p-value = 0.0001863
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 39.201, df = 14, p-value = 0.0003396
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 39.933, df = 15, p-value = 0.0004642
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 44.033, df = 16, p-value = 0.000195
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 51.866, df = 17, p-value = 2.158e-05
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 52.269, df = 18, p-value = 3.402e-05
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 52.273, df = 19, p-value = 6.021e-05
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 54.393, df = 20, p-value = 5.057e-05
##
##
## [1] "PeriphytonCoverage"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.021773, df = 1, p-value = 0.8827
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.064528, df = 2, p-value = 0.9683
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.23089, df = 3, p-value = 0.9725
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.84886, df = 4, p-value = 0.9318
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.88279, df = 5, p-value = 0.9715
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.95017, df = 6, p-value = 0.9874
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.8164, df = 7, p-value = 0.9693
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.6045, df = 8, p-value = 0.9567
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.6647, df = 9, p-value = 0.9761
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.6655, df = 10, p-value = 0.9882
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.004, df = 11, p-value = 0.9907
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.0848, df = 12, p-value = 0.9949
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.106, df = 13, p-value = 0.9975
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.2544, df = 14, p-value = 0.9985
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.007, df = 15, p-value = 0.9977
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.1451, df = 16, p-value = 0.9986
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.2192, df = 17, p-value = 0.9993
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.4268, df = 18, p-value = 0.998
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.7599, df = 19, p-value = 0.9984
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.9832, df = 20, p-value = 0.9967
##
##
## [1] "SurroundingMaterial"
## [[1]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.15293, df = 1, p-value = 0.6957
##
##
## [[2]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.23062, df = 2, p-value = 0.8911
##
##
## [[3]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 0.54662, df = 3, p-value = 0.9085
##
##
## [[4]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.3671, df = 4, p-value = 0.8499
##
##
## [[5]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 1.7633, df = 5, p-value = 0.8808
##
##
## [[6]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.0492, df = 6, p-value = 0.9151
##
##
## [[7]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.2462, df = 7, p-value = 0.945
##
##
## [[8]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.9715, df = 8, p-value = 0.9361
##
##
## [[9]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 2.9864, df = 9, p-value = 0.9648
##
##
## [[10]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.1123, df = 10, p-value = 0.9787
##
##
## [[11]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.2476, df = 11, p-value = 0.987
##
##
## [[12]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 3.6398, df = 12, p-value = 0.9891
##
##
## [[13]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.0642, df = 13, p-value = 0.9905
##
##
## [[14]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 4.1087, df = 14, p-value = 0.9948
##
##
## [[15]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 5.8848, df = 15, p-value = 0.9816
##
##
## [[16]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 6.1652, df = 16, p-value = 0.9862
##
##
## [[17]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 7.5438, df = 17, p-value = 0.9754
##
##
## [[18]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 8.9603, df = 18, p-value = 0.9607
##
##
## [[19]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.6168, df = 19, p-value = 0.9618
##
##
## [[20]]
##
## Box-Ljung test
##
## data: resid(auto.arima)
## X-squared = 9.619, df = 20, p-value = 0.9746
##Releases Notes What’s New, Updated, or Fixed in This Release
New
Updated
Fixed
CABIN_vv_habitat.Rmd Version 1.1 — November 1st, 2017
Added suggestions of actions to help in the verification and validation of habitat data.
Actions — Added suggestions of actions to help in the verification and validation of habitat data.
CABIN_vv_habitat.Rmd Version 1.0 — August 18, 2017
First completed version.
Developed by Martin Jean and Evelyne Paquette-Boisclair